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The field of natural language processing (NLP) has witnessed significant progress in recent years, with a notable focus on improving large language models' (LLM) performance through innovative prompting techniques.
Graph Processing on FPGAs: Taxonomy, Survey, Challenges, Apr. 2019
M. Besta, D. Stanojevic, J. De Fine Licht, T. Ben-Nun, and T. Hoefler · 1903
Earlier work this paper cites.
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks, Aug. 2020
M. Wang, D. Zheng, Z. Ye, Q. Gan, M. Li, X. Song, J. Zhou, C. Ma, L. Yu, Y. Gai, T. Xiao, T. He, G. Karypis, J. Li, and Z. Zhang · 1909
Earlier work this paper cites.
Classification and Regression Trees
Leo Breiman, Jerome Friedman, Charles J. Stone, R.A. Olshen · 1984
Earlier work this paper cites.
Experiments with a New Boosting Algorithm
Y. Freund and R. E. Schapire · 1996
Earlier work this paper cites.
Flattened Butterfly: A Cost-Efficient Topology for High-Radix Networks
J. Kim, W. J. Dally, and D. Abts · 2007
Earlier work this paper cites.
Survey of Graph Database Models
R. Angles and C. Gutierrez · 2008
Earlier work this paper cites.
Technology-Driven, Highly-Scalable Dragonfly Topology
J. Kim, W. J. Dally, S. Scott, and D. Abts · 2008
Earlier work this paper cites.
Mining Heterogeneous Information Networks: Principles and Methodologies
Y. Sun and J. Han · 2012
Earlier work this paper cites.
Enabling Highly-Scalable Remote Memory Access Programming with MPI-3 One Sided
R. Gerstenberger, M. Besta, and T. Hoefler · 2013
Earlier work this paper cites.
Slim Fly: A Cost Effective Low-Diameter Network Topology
M. Besta and T. Hoefler · 2014
Earlier work this paper cites.
Learning to Solve Arithmetic Word Problems with Verb Categorization
M. J. Hosseini, H. Hajishirzi, O. Etzioni, and N. Kushman · 2014
Earlier work this paper cites.
The Stanford CoreNLP Natural Language Processing Toolkit
C. Manning, M. Surdeanu, J. Bauer, J. Finkel, S. Bethard, and D. McClosky · 2014
Earlier work this paper cites.
PIM-Enabled Instructions: A Low-Overhead, Locality-Aware Processing-In-Memory Architecture
J. Ahn, S. Yoo, O. Mutlu, and K. Choi · 2015
Earlier work this paper cites.
Leveraging Linguistic Structure for Open Domain Information Extraction
G. Angeli, M. J. Johnson Premkumar, and C. D. Manning · 2015
Earlier work this paper cites.
Active Access: A Mechanism for High-Performance Distributed Data-Centric Computations
M. Besta and T. Hoefler · 2015
Earlier work this paper cites.
Solving General Arithmetic Word Problems
S. Roy and D. Roth · 2015
Earlier work this paper cites.
Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems, Apr. 2016
J. Dodge, A. Gane, X. Zhang, A. Bordes, S. Chopra, A. Miller, A. Szlam, and J. Weston · 2016
Earlier work this paper cites.
MAWPS: A Math Word Problem Repository
R. Koncel-Kedziorski, S. Roy, A. Amini, N. Kushman, and H. Hajishirzi · 2016
Earlier work this paper cites.
Simpler Context-Dependent Logical Forms via Model Projections
R. Long, P. Pasupat, and P. Liang · 2016
Earlier work this paper cites.
Psychological Studies of Thought: Thoughts about a Concept of Thought
V. Shadrikov, S. Kurginyan, and O. Martynova · 2016
Earlier work this paper cites.
To Push or To Pull: On Reducing Communication and Synchronization in Graph Computations
M. Besta, M. Podstawski, L. Groner, E. Solomonik, and T. Hoefler · 2017
Earlier work this paper cites.
Geometric Deep Learning: Going Beyond Euclidean Data
M. M. Bronstein, J. Bruna, Y. LeCun, A. Szlam, and P. Vandergheynst · 2017
Earlier work this paper cites.
Representation Learning on Graphs: Methods and Applications
W. L. Hamilton, R. Ying, and J. Leskovec · 2017
Earlier work this paper cites.
Semi-Supervised Classification with Graph Convolutional Network
T. N. Kipf and M. Welling · 2017
Earlier work this paper cites.
Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems
W. Ling, D. Yogatama, C. Dyer, and P. Blunsom · 2017
Earlier work this paper cites.
Ambit: In-Memory Accelerator for Bulk Bitwise Operations Using Commodity DRAM Technology
V. Seshadri, D. Lee, T. Mullins, H. Hassan, A. Boroumand, J. Kim, M. A. Kozuch, O. Mutlu, P. B. Gibbons, and T. C. Mowry · 2017
Earlier work this paper cites.
A Corpus of Natural Language for Visual Reasoning
A. Suhr, M. Lewis, J. Yeh, and Y. Artzi · 2017
Earlier work this paper cites.
An Introduction to Graph Data Management
R. Angles and C. Gutierrez · 2018
Earlier work this paper cites.
Slim NoC: A Low-Diameter On-Chip Network Topology for High Energy Efficiency and Scalability
M. Besta, S. M. Hassan, S. Yalamanchili, R. Ausavarungnirun, O. Mutlu, and T. Hoefler · 2018
Earlier work this paper cites.
Log(Graph): A Near-Optimal High-Performance Graph Representation
M. Besta, D. Stanojevic, T. Zivic, J. Singh, M. Hoerold, and T. Hoefler · 2018
Earlier work this paper cites.
Data Models
A. Bonifati, G. Fletcher, H. Voigt, and N. Yakovets · 2018
Earlier work this paper cites.
A Survey on NoSQL Stores
A. Davoudian, L. Chen, and M. Liu · 2018
Earlier work this paper cites.
Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks
B. Lake and M. Baroni · 2018
Earlier work this paper cites.
HotpotQA: A Dataset for Diverse, Explainable Multi-Hop Question Answering
Z. Yang, P. Qi, S. Zhang, Y. Bengio, W. Cohen, R. Salakhutdinov, and C. D. Manning · 2018
Earlier work this paper cites.
MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms
A. Amini, S. Gabriel, S. Lin, R. Koncel-Kedziorski, Y. Choi, and H. Hajishirzi · 2019
Earlier work this paper cites.
Network-Accelerated Non-Contiguous Memory Transfers
S. Di Girolamo, K. Taranov, A. Kurth, M. Schaffner, T. Schneider, J. Beránek, M. Besta, L. Benini, D. Roweth, and T. Hoefler · 2019
Earlier work this paper cites.
DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs
D. Dua, Y. Wang, P. Dasigi, G. Stanovsky, S. Singh, and M. Gardner · 2019
Earlier work this paper cites.
Fast Graph Representation Learning with PyTorch Geometric
M. Fey and J. E. Lenssen · 2019
Earlier work this paper cites.
Processing-In-Memory: A Workload-Driven Perspective
S. Ghose, A. Boroumand, J. S. Kim, J. Gómez-Luna, and O. Mutlu · 2019
Earlier work this paper cites.
Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering
Y. Goyal, T. Khot, A. Agrawal, D. Summers-Stay, D. Batra, and D. Parikh · 2019
Earlier work this paper cites.
Processing Data Where It Makes Sense: Enabling In-Memory Computation
O. Mutlu, S. Ghose, J. Gómez-Luna, and R. Ausavarungnirun · 2019
Earlier work this paper cites.
PIE: A Large-Scale Dataset and Models for Pedestrian Intention Estimation and Trajectory Prediction
A. Rasouli, I. Kotseruba, T. Kunic, and J. Tsotsos · 2019
Earlier work this paper cites.
CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge
A. Talmor, J. Herzig, N. Lourie, and J. Berant · 2019
Earlier work this paper cites.
Heterogeneous Graph Neural Network
C. Zhang, D. Song, C. Huang, A. Swami, and N. V. Chawla · 2019
Earlier work this paper cites.
High-Performance Parallel Graph Coloring with Strong Guarantees on Work, Depth, and Quality
M. Besta, A. Carigiet, K. Janda, Z. Vonarburg-Shmaria, L. Gianinazzi, and T. Hoefler · 2020
Earlier work this paper cites.
Substream-Centric Maximum Matchings on FPGA
M. Besta, M. Fischer, T. Ben-Nun, D. Stanojevic, J. De Fine Licht, and T. Hoefler · 2020
Earlier work this paper cites.
Language Models are Few-Shot Learners
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, S. Agarwal, A. Herbert-Voss, G. Krueger, T. Henighan, R. Child, A. Ramesh, D. Ziegler, J. Wu, C. Winter, C. Hesse, M. Chen, E. Sigler, M. Litwin, S. Gray, B. Chess, J. Clark, C. Berner, S. McCandlish, A. Radford, I. Sutskever, and D. Amodei · 2020
Earlier work this paper cites.
Transformations of High-Level Synthesis Codes for High-Performance Computing
J. De Fine Licht, M. Besta, S. Meierhans, and T. Hoefler · 2020
Earlier work this paper cites.
A Dataset and Baselines for Visual Question Answering on Art
N. Garcia, C. Ye, Z. Liu, Q. Hu, M. Otani, C. Chu, Y. Nakashima, and T. Mitamura · 2020
Earlier work this paper cites.
Constructing A Multi-Hop QA Dataset for Comprehensive Evaluation of Reasoning Steps
X. Ho, A.-K. Duong Nguyen, S. Sugawara, and A. Aizawa · 2020
Earlier work this paper cites.
Measuring Compositional Generalization: A Comprehensive Method on Realistic Data
D. Keysers, N. Schärli, N. Scales, H. Buisman, D. Furrer, S. Kashubin, N. Momchev, D. Sinopalnikov, L. Stafiniak, T. Tihon, D. Tsarkov, X. Wang, M. van Zee, and O. Bousquet · 2020
Earlier work this paper cites.
COGS: A Compositional Generalization Challenge Based on Semantic Interpretation
N. Kim and T. Linzen · 2020
Earlier work this paper cites.
PyTorch Distributed: Experiences on Accelerating Data Parallel Training
S. Li, Y. Zhao, R. Varma, O. Salpekar, P. Noordhuis, T. Li, A. Paszke, J. Smith, B. Vaughan, P. Damania, and S. Chintala · 2020
Earlier work this paper cites.
A Survey of FPGA-based Accelerators for Convolutional Neural Networks
S. Mittal · 2020
Earlier work this paper cites.
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
C. Raffel, N. Shazeer, A. Roberts, K. Lee, S. Narang, M. Matena, Y. Zhou, W. Li, and P. J. Liu · 2020
Earlier work this paper cites.
Graph Neural Networks: A Review of Methods and Applications
J. Zhou, G. Cui, S. Hu, Z. Zhang, C. Yang, Z. Liu, L. Wang, C. Li, and M. Sun · 2020
Earlier work this paper cites.
Program Synthesis with Large Language Models, Aug. 2021
J. Austin, A. Odena, M. Nye, M. Bosma, H. Michalewski, D. Dohan, E. Jiang, C. Cai, M. Terry, Q. Le, and C. Sutton · 2021
Earlier work this paper cites.
Quantum Accelerator Stack: A Research Roadmap, May 2021
K. Bertels, A. Sarkar, A. Krol, R. Budhrani, J. Samadi, E. Geoffroy, J. Matos, R. Abreu, G. Gielen, and I. Ashraf · 2021
Earlier work this paper cites.
SISA: Set-Centric Instruction Set Architecture for Graph Mining on Processing-in-Memory Systems
M. Besta, R. Kanakagiri, G. Kwaśniewski, R. Ausavarungnirun, J. Beránek, K. Kanellopoulos, K. Janda, Z. Vonarburg-Shmaria, L. Gianinazzi, I. Stefan, J. G. Luna, J. Golinowski, M. Copik, L. Kapp-Schwoerer, S. Di Girolamo, N. Blach, M. Konieczny, O. Mutlu, and T. Hoefler · 2021
Earlier work this paper cites.
GraphMineSuite: Enabling High-Performance and Programmable Graph Mining Algorithms with Set Algebra
M. Besta, Z. Vonarburg-Shmaria, Y. Schaffner, L. Schwarz, G. Kwaśniewski, L. Gianinazzi, J. Beranek, K. Janda, T. Holenstein, S. Leisinger, P. Tatkowski, E. Ozdemir, A. Balla, M. Copik, P. Lindenberger, M. Konieczny, O. Mutlu, and T. Hoefler · 2021
Earlier work this paper cites.
Evaluating Large Language Models Trained on Code, July 2021
M. Chen, J. Tworek, H. Jun, Q. Yuan, H. P. de Oliveira Pinto, J. Kaplan, H. Edwards, Y. Burda, N. Joseph, G. Brockman, A. Ray, R. Puri, G. Krueger, M. Petrov, H. Khlaaf, G. Sastry, P. Mishkin, B. Chan, S. Gray, N. Ryder, M. Pavlov, A. Power, L. Kaiser, M. Bavarian, C. Winter, P. Tillet, F. P. Such, D. Cummings, M. Plappert, F. Chantzis, E. Barnes, A. Herbert-Voss, W. H. Guss, A. Nichol, A. Paino, N. Tezak, J. Tang, I. Babuschkin, S. Balaji, S. Jain, W. Saunders, C. Hesse, A. N. Carr, J. Leike, J. Achiam, V. Misra, E. Morikawa, A. Radford, M. Knight, M. Brundage, M. Murati, K. Mayer, P. Welinder, B. McGrew, D. Amodei, S. McCandlish, I. Sutskever, and W. Zaremba · 2021
Earlier work this paper cites.
FinQA: A Dataset of Numerical Reasoning over Financial Data
Z. Chen, W. Chen, C. Smiley, S. Shah, I. Borova, D. Langdon, R. Moussa, M. Beane, T.-H. Huang, B. Routledge, and W. Y. Wang · 2021
Earlier work this paper cites.
Training Verifiers to Solve Math Word Problems, Nov. 2021
K. Cobbe, V. Kosaraju, M. Bavarian, M. Chen, H. Jun, L. Kaiser, M. Plappert, J. Tworek, J. Hilton, R. Nakano, C. Hesse, and J. Schulman · 2021
Earlier work this paper cites.
SeBS: A Serverless Benchmark Suite for Function-as-a-Service Computing
M. Copik, G. Kwaśniewski, M. Besta, M. Podstawski, and T. Hoefler · 2021
Earlier work this paper cites.
Explaining Answers with Entailment Trees
B. Dalvi, P. Jansen, O. Tafjord, Z. Xie, H. Smith, L. Pipatanangkura, and P. Clark · 2021
Earlier work this paper cites.
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies
M. Geva, D. Khashabi, E. Segal, T. Khot, D. Roth, and J. Berant · 2021
Earlier work this paper cites.
Parallel Algorithms for Finding Large Cliques in Sparse Graphs
L. Gianinazzi, M. Besta, Y. Schaffner, and T. Hoefler · 2021
Earlier work this paper cites.
Measuring Massive Multitask Language Understanding
D. Hendrycks, C. Burns, S. Basart, A. Zou, M. Mazeika, D. Song, and J. Steinhardt · 2021
Earlier work this paper cites.
Measuring Mathematical Problem Solving with the MATH Dataset
D. Hendrycks, C. Burns, S. Kadavath, A. Arora, S. Basart, E. Tang, D. Song, and J. Steinhardt · 2021
Earlier work this paper cites.
LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning
J. Liu, L. Cui, H. Liu, D. Huang, Y. Wang, and Y. Zhang · 2021
Earlier work this paper cites.
Are NLP Models Really Able to Solve Simple Math Word Problems?
A. Patel, S. Bhattamishra, and N. Goyal · 2021
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CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks, Aug. 2021
R. Puri, D. S. Kung, G. Janssen, W. Zhang, G. Domeniconi, V. Zolotov, J. Dolby, J. Chen, M. Choudhury, L. Decker, V. Thost, L. Buratti, S. Pujar, S. Ramji, U. Finkler, S. Malaika, and F. Reiss · 2021
Earlier work this paper cites.
ALFWorld: Aligning Text and Embodied Environments for Interactive Learning
M. Shridhar, X. Yuan, M.-A. Côté, Y. Bisk, A. Trischler, and M. Hausknecht · 2021
Earlier work this paper cites.
The Neural Correlates of Ongoing Conscious Thought
J. Smallwood, A. Turnbull, H. Wang, N. S. Ho, G. L. Poerio, T. Karapanagiotidis, D. Konu, B. Mckeown, M. Zhang, C. Murphy, D. Vatansever, D. Bzdok, M. Konishi, R. Leech, P. Seli, J. W. Schooler, B. Bernhardt, D. S. Margulies, and E. Jefferies · 2021
Earlier work this paper cites.
ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language
O. Tafjord, B. Dalvi, and P. Clark · 2021
Earlier work this paper cites.
Knowledge Enhanced Pretrained Language Models: A Comprehensive Survey, Oct. 2021
X. Wei, S. Wang, D. Zhang, P. Bhatia, and A. Arnold · 2021
Earlier work this paper cites.
A Comprehensive Survey on Graph Neural Networks
Z. Wu, S. Pan, F. Chen, G. Long, C. Zhang, and P. S. Yu · 2021
Earlier work this paper cites.
Motif Prediction with Graph Neural Networks
M. Besta, R. Grob, C. Miglioli, N. Bernold, G. Kwaśniewski, G. Gjini, R. Kanakagiri, S. Ashkboos, L. Gianinazzi, N. Dryden, and T. Hoefler · 2022
Earlier work this paper cites.
Neural Graph Databases
M. Besta, P. Iff, F. Scheidl, K. Osawa, N. Dryden, M. Podstawski, T. Chen, and T. Hoefler · 2022
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ProbGraph: High-Performance and High-Accuracy Graph Mining with Probabilistic Set Representations
M. Besta, C. Miglioli, P. Sylos Labini, J. Tětek, P. Iff, R. Kanakagiri, S. Ashkboos, K. Janda, M. Podstawski, G. Kwaśniewski, N. Gleinig, F. Vella, O. Mutlu, and T. Hoefler · 2022
Earlier work this paper cites.
Improving Language Model Predictions via Prompts Enriched with Knowledge Graphs
R. Brate, M.-H. Dang, F. Hoppe, Y. He, A. Meroño-Peñuela, and V. Sadashivaiah · 2022
Earlier work this paper cites.
Machine Learning on Graphs: A Model and Comprehensive Taxonomy
I. Chami, S. Abu-El-Haija, B. Perozzi, C. Ré, and K. Murphy · 2022
Cited alongside, same era.
MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text
W. Chen, H. Hu, X. Chen, P. Verga, and W. Cohen · 2022
Cited alongside, same era.
ConvFinQA: Exploring the Chain of Numerical Reasoning in Conversational Finance Question Answering
Z. Chen, S. Li, C. Smiley, Z. Ma, S. Shah, and W. Y. Wang · 2022
Cited alongside, same era.
Faithful Reasoning Using Large Language Models, Aug. 2022
A. Creswell and M. Shanahan · 2022
Cited alongside, same era.
Building Blocks for Network-Accelerated Distributed File Systems
S. Di Girolamo, D. De Sensi, K. Taranov, M. Malesevic, M. Besta, T. Schneider, S. Kistler, and T. Hoefler · 2022
Cited alongside, same era.
Graph Prompt Learning: A Comprehensive Survey and Beyond, Nov. 2023
X. Sun, J. Zhang, X. Wu, H. Cheng, Y. Xiong, and J. Li · 2023
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Large Language Models in Medicine
A. J. Thirunavukarasu, D. S. J. Ting, K. Elangovan, L. Gutierrez, T. F. Tan, and D. S. W. Ting · 2023
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Can Language Models Solve Graph Problems in Natural Language?
H. Wang, S. Feng, T. He, Z. Tan, X. Han, and Y. Tsvetkov · 2023
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Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models
L. Wang, W. Xu, Y. Lan, Z. Hu, Y. Lan, R. K.-W. Lee, and E.-P. Lim · 2023
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Self-Consistency Improves Chain of Thought Reasoning in Language Models
X. Wang, J. Wei, D. Schuurmans, Q. Le, E. Chi, and D. Zhou · 2023
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Successive Prompting for Decomposing Complex Questions
D. Dua, S. Gupta, S. Singh, and M. Gardner · 2022
Cited alongside, same era.
Learning Combinatorial Node Labeling Algorithms, May 2022
L. Gianinazzi, M. Fries, N. Dryden, T. Ben-Nun, M. Besta, and T. Hoefler · 2022
Cited alongside, same era.
Vision-and-Language Navigation: A Survey of Tasks, Methods, and Future Directions
J. Gu, E. Stefani, Q. Wu, J. Thomason, and X. Wang · 2022
Cited alongside, same era.
A Survey on Improving NLP Models with Human Explanations
M. Hartmann and D. Sonntag · 2022
Cited alongside, same era.
Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations
J. Jung, L. Qin, S. Welleck, F. Brahman, C. Bhagavatula, R. Le Bras, and Y. Choi · 2022
Cited alongside, same era.
Hey AI, Can You Solve Complex Tasks by Talking to Agents?
T. Khot, K. Richardson, D. Khashabi, and A. Sabharwal · 2022
Cited alongside, same era.
Large Language Models Are Zero-Shot Reasoners
T. Kojima, S. S. Gu, M. Reid, Y. Matsuo, and Y. Iwasawa · 2022
Cited alongside, same era.
X. Wang, Q. Yang, Y. Qiu, J. Liang, Q. He, Z. Gu, Y. Xiao, and W. Wang · 2023
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Describe, Explain, Plan and Select: Interactive Planning with LLMs Enables Open-World Multi-Task Agents
Z. Wang, S. Cai, G. Chen, A. Liu, X. S. Ma, and Y. Liang · 2023
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Interactive Natural Language Processing, May 2023
Z. Wang, G. Zhang, K. Yang, N. Shi, W. Zhou, S. Hao, G. Xiong, Y. Li, M. Y. Sim, X. Chen, Q. Zhu, Z. Yang, A. Nik, Q. Liu, C. Lin, S. Wang, R. Liu, W. Chen, K. Xu, D. Liu, Y. Guo, and J. Fu · 2023
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Large Language Models Are Better Reasoners with Self-Verification
Y. Weng, M. Zhu, F. Xia, B. Li, S. He, S. Liu, B. Sun, K. Liu, and J. Zhao · 2023
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System 2 Attention (Is Something You Might Need Too), Nov. 2023
J. Weston and S. Sukhbaatar · 2023
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The Learnability of In-Context Learning
N. Wies, Y. Levine, and A. Shashua · 2023
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A Survey of Graph Prompting Methods: Techniques, Applications, and Challenges, May 2023
X. Wu, K. Zhou, M. Sun, X. Wang, and N. Liu · 2023
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Self-Evaluation Guided Beam Search for Reasoning
Y. Xie, K. Kawaguchi, Y. Zhao, J. X. Zhao, M.-Y. Kan, J. He, and M. Xie · 2023
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k k NN Prompting: Beyond-Context Learning with Calibration-Free Nearest Neighbor Inference
B. Xu, Q. Wang, Z. Mao, Y. Lyu, Q. She, and Y. Zhang · 2023
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F. Yao, C. Tian, J. Liu, Z. Zhang, Q. Liu, L. Jin, S. Li, X. Li, and X. Sun · 2023
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Tree of Thoughts: Deliberate Problem Solving with Large Language Models
S. Yao, D. Yu, J. Zhao, I. Shafran, T. Griffiths, Y. Cao, and K. Narasimhan · 2023
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ReAct: Synergizing Reasoning and Acting in Language Models
S. Yao, J. Zhao, D. Yu, N. Du, I. Shafran, K. R. Narasimhan, and Y. Cao · 2023
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Large Language Models Are Versatile Decomposers: Decomposing Evidence and Questions for Table-Based Reasoning
Y. Ye, B. Hui, M. Yang, B. Li, F. Huang, and Y. Li · 2023
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Forward Looking Active Retrieval Augmented Generation
L. Zeit-Altpeter · 2023
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On the Paradox of Learning to Reason from Data
H. Zhang, L. H. Li, T. Meng, K.-W. Chang, and G. V. den Broeck · 2023
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J. Zhang · 2023
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Graph Meets LLMs: Towards Large Graph Models
Z. Zhang, H. Li, Z. Zhang, Y. Qin, X. Wang, and W. Zhu · 2023
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Z. Zhang, Y. Yao, A. Zhang, X. Tang, X. Ma, Z. He, Y. Wang, M. Gerstein, R. Wang, G. Liu, and H. Zhao · 2023
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Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
L. Zheng, W.-L. Chiang, Y. Sheng, S. Zhuang, Z. Wu, Y. Zhuang, Z. Lin, Z. Li, D. Li, E. Xing, H. Zhang, J. E. Gonzalez, and I. Stoica · 2023
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Least-to-Most Prompting Enables Complex Reasoning in Large Language Models
D. Zhou, N. Schärli, L. Hou, J. Wei, N. Scales, X. Wang, D. Schuurmans, C. Cui, O. Bousquet, Q. V. Le, and E. H. Chi · 2023
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Self-RAG: Learning to Retrieve, Generate, and Critique Through Self-Reflection
A. Asai, Z. Wu, Y. Wang, A. Sil, and H. Hajishirzi · 2024
Closest in time.
Graph of Thoughts: Solving Elaborate Problems with Large Language Models
M. Besta, N. Blach, A. Kubicek, R. Gerstenberger, L. Gianinazzi, J. Gajda, T. Lehmann, M. Podstawski, H. Niewiadomski, P. Nyczyk, and T. Hoefler · 2024
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GDI: A Graph Database Interface Standard
M. Besta, R. Gerstenberger, N. Blach, M. Fischer, and T. Hoefler · 2024
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Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysis
M. Besta and T. Hoefler · 2024
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GraphReason: Enhancing Reasoning Capabilities of Large Language Models Through a Graph-Based Verification Approach
L. Cao · 2024
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B. Chen, Z. Zhang, N. Langrené, and S. Zhu · 2024
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Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
Z. Chen, H. Mao, H. Li, W. Jin, H. Wen, X. Wei, S. Wang, D. Yin, W. Fan, H. Liu, and J. Tang · 2024
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Navigate Through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future
Z. Chu, J. Chen, Q. Chen, W. Yu, T. He, H. Wang, W. Peng, M. Liu, B. Qin, and T. Liu · 2024
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Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation
R. Ding, C. Zhang, L. Wang, Y. Xu, M. Ma, W. Zhang, S. Qin, S. Rajmohan, Q. Lin, and D. Zhang · 2024
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Towards Foundation Models for Knowledge Graph Reasoning
M. Galkin, X. Yuan, H. Mostafa, J. Tang, and Z. Zhu · 2024
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Retrieval-Augmented Generation for Large Language Models: A Survey, Mar. 2024
Y. Gao, Y. Xiong, X. Gao, K. Jia, J. Pan, Y. Bi, Y. Dai, J. Sun, and H. Wang · 2024
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FOLIO: Natural Language Reasoning with First-Order Logic
S. Han, H. Schoelkopf, Y. Zhao, Z. Qi, M. Riddell, W. Zhou, J. Coady, D. Peng, Y. Qiao, L. Benson, L. Sun, A. Wardle-Solano, H. Szabó, E. Zubova, M. Burtell, J. Fan, Y. Liu, B. Wong, M. Sailor, A. Ni, L. Nan, J. Kasai, T. Yu, R. Zhang, A. Fabbri, W. M. Kryscinski, S. Yavuz, Y. Liu, X. V. Lin, S. Joty, Y. Zhou, C. Xiong, R. Ying, A. Cohan, and D. Radev · 2024
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Chain-of-Symbol Prompting Elicits Planning in Large Language Models, Aug. 2024
H. Hu, H. Lu, H. Zhang, W. Lam, and Y. Zhang · 2024
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A Survey of Knowledge Enhanced Pre-Trained Language Models
L. Hu, Z. Liu, Z. Zhao, L. Hou, L. Nie, and J. Li · 2024
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Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why
J. Huang, X. Zhang, Q. Mei, and J. Ma · 2024
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RESPROMPT: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models
S. Jiang, Z. Shakeri, A. Chan, M. Sanjabi, H. Firooz, Y. Xia, B. Akyildiz, Y. Sun, J. Li, Q. Wang, and A. Celikyilmaz · 2024
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Large Language Models on Graphs: A Comprehensive Survey
B. Jin, G. Liu, C. Han, M. Jiang, H. Ji, and J. Han · 2024
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An LLM Compiler for Parallel Function Calling
S. Kim, S. Moon, R. Tabrizi, N. Lee, M. W. Mahoney, K. Keutzer, and A. Gholami · 2024
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PolarStar: Expanding the Horizon of Diameter-3 Networks
K. Lakhotia, L. Monroe, K. Isham, M. Besta, N. Blach, T. Hoefler, and F. Petrini · 2024
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A Survey of Graph Meets Large Language Model: Progress and Future Directions
Y. Li, Z. Li, P. Wang, J. Li, X. Sun, H. Cheng, and J. X. Yu · 2024
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BatchPrompt: Accomplish More with Less
J. Lin, M. Diesendruck, L. Du, and R. Abraham · 2024
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Towards Graph Foundation Models: A Survey and Beyond, July 2024
J. Liu, C. Yang, Z. Lu, J. Chen, Y. Li, M. Zhang, T. Bai, Y. Fang, L. Sun, P. S. Yu, and C. Shi · 2024
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ControlLLM: Augment Language Models with Tools by Searching on Graphs
Z. Liu, Z. Lai, Z. Gao, E. Cui, Z. Li, X. Zhu, L. Lu, Q. Chen, Y. Qiao, J. Dai, and W. Wang · 2024
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Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning
L. Luo, Y.-F. Li, G. Haffari, and S. Pan · 2024
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Direct Evaluation of Chain-of-Thought in Multi-Hop Reasoning with Knowledge Graphs
M.-V. Nguyen, L. Luo, F. Shiri, D. Phung, Y.-F. Li, T.-T. Vu, and G. Haffari · 2024
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Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
X. Ning, Z. Lin, Z. Zhou, Z. Wang, H. Yang, and Y. Wang · 2024
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Unifying Large Language Models and Knowledge Graphs: A Roadmap
S. Pan, L. Luo, Y. Wang, C. Chen, J. Wang, and X. Wu · 2024
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Integrating Graphs with Large Language Models: Methods and Prospects
S. Pan, Y. Zheng, and Y. Liu · 2024
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AutoGPT: build & use AI agents - Github
T. B. Richards · 2024
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Branch-Solve-Merge Improves Large Language Model Evaluation and Generation
S. Saha, O. Levy, A. Celikyilmaz, M. Bansal, J. Weston, and X. Li · 2024
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Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models
B. Sel, A. Tawaha, V. Khattar, R. Jia, and M. Jin · 2024
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Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
J. Sun, C. Xu, L. Tang, S. Wang, C. Lin, Y. Gong, L. Ni, H.-Y. Shum, and J. Guo · 2024
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GraphGPT: Graph Instruction Tuning for Large Language Models
J. Tang, Y. Yang, W. Wei, L. Shi, L. Su, S. Cheng, D. Yin, and C. Huang · 2024
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Graph Neural Prompting with Large Language Models
Y. Tian, H. Song, Z. Wang, H. Wang, Z. Hu, F. Wang, N. V. Chawla, and P. Xu · 2024
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Why Can Large Language Models Generate Correct Chain-of-Thoughts?, June 2024
R. Tutunov, A. Grosnit, J. Ziomek, J. Wang, and H. Bou-Ammar · 2024
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Graph Neural Architecture Search with GPT-4, Mar. 2024
H. Wang, Y. Gao, X. Zheng, P. Zhang, H. Chen, and J. Bu · 2024
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Knowledge Graph Prompting for Multi-Document Question Answering
Y. Wang, N. Lipka, R. A. Rossi, A. Siu, R. Zhang, and T. Derr · 2024
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MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models
Y. Wen, Z. Wang, and J. Sun · 2024
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WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions
C. Xu, Q. Sun, K. Zheng, X. Geng, P. Zhao, J. Feng, C. Tao, Q. Lin, and D. Jiang · 2024
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A Survey of Knowledge Enhanced Pre-Trained Language Models
J. Yang, X. Hu, G. Xiao, and Y. Shen · 2024
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Give us the Facts: Enhancing Large Language Models With Knowledge Graphs for Fact-Aware Language Modeling
L. Yang, H. Chen, Z. Li, X. Ding, and X. Wu · 2024
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GoT: Effective Graph-of-Thought Reasoning in Language Models
Y. Yao, Z. Li, and H. Zhao · 2024
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Language Is All a Graph Needs
R. Ye, C. Zhang, R. Wang, S. Xu, and Y. Zhang · 2024
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Thought Propagation: An Analogical Approach to Complex Reasoning with Large Language Models
J. Yu, R. He, and R. Ying · 2024
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Making Large Language Models Perform Better in Knowledge Graph Completion
Y. Zhang, Z. Chen, L. Guo, Y. Xu, W. Zhang, and H. Chen · 2024
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Small Language Models Need Strong Verifiers to Self-Correct Reasoning
Y. Zhang, M. Khalifa, L. Logeswaran, J. Kim, M. Lee, H. Lee, and L. Wang · 2024
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LLM4DyG: Can Large Language Models Solve Spatial-Temporal Problems on Dynamic Graphs?
Z. Zhang, X. Wang, Z. Zhang, H. Li, Y. Qin, and W. Zhu · 2024
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GraphText: Graph Reasoning in Text Space
J. Zhao, L. Zhuo, Y. Shen, M. Qu, K. Liu, M. Bronstein, Z. Zhu, and J. Tang · 2024
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Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models Through Logic
X. Zhao, M. Li, W. Lu, C. Weber, J. H. Lee, K. Chu, and S. Wermter · 2024
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LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities
Y. Zhu, X. Wang, J. Chen, S. Qiao, Y. Ou, Y. Yao, S. Deng, H. Chen, and N. Zhang · 2024
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Self-Supervised Multimodal Learning: A Survey
Y. Zong, O. M. Aodha, and T. Hospedales · 2024
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Data-Centric Graph Learning: A Survey
Y. Guo, D. Bo, C. Yang, Z. Lu, Z. Zhang, J. Liu, Y. Peng, and C. Shi · 2025
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OCEAN: Offline Chain-of-Thought Evaluation and Alignment in Large Language Models
J. Wu, X. Li, R. Wang, Y. Xia, Y. Xiong, J. Wang, T. Yu, X. Chen, B. Kveton, L. Yao, J. Shang, and J. McAuley · 2025
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Cumulative Reasoning with Large Language Models
Y. Zhang, J. Yang, Y. Yuan, and A. C. Yao · 2025
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A Survey of Large Language Models, Mar. 2025
W. X. Zhao, K. Zhou, J. Li, T. Tang, X. Wang, Y. Hou, Y. Min, B. Zhang, J. Zhang, Z. Dong, Y. Du, C. Yang, Y. Chen, Z. Chen, J. Jiang, R. Ren, Y. Li, X. Tang, Z. Liu, P. Liu, J.-Y. Nie, and J.-R. Wen · 2025
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