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Recent advances in test-time scaling have shown promising results in improving Large Language Model (LLM) performance through strategic computation allocation during inference.
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Abstractive summarization of product reviews using discourse structure
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Abstractive summarization of spoken and written conversations based on phrasal queries
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Alexander Fabbri, Irene Li, Tianwei She, Suyi Li, and Dragomir Radev. 2019 · 2019
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Hierarchical transformers for multi-document summarization
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Metrics also disagree in the low scoring range: Revisiting summarization evaluation metrics
Manik Bhandari, Pranav Narayan Gour, Atabak Ashfaq, and Pengfei Liu. 2020 · 2020
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 2020
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Training verifiers to solve math word problems
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Bartscore: Evaluating generated text as text generation
Weizhe Yuan, Graham Neubig, and Pengfei Liu. 2021 · 2021
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Ask me anything: A simple strategy for prompting language models
Simran Arora, Avanika Narayan, Mayee F. Chen, Laurel Orr, Neel Guha, Kush Bhatia, Ines Chami, Frederic Sala, and Christopher Ré. 2022 · 2022
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Scaling laws for reward model overoptimization
Leo Gao, John Schulman, and Jacob Hilton. 2022 · 2022
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Open domain multi-document summarization: A comprehensive study of model brittleness under retrieval
John Giorgi, Luca Soldaini, Bo Wang, Gary Bader, Kyle Lo, Lucy Lu Wang, and Arman Cohan. 2022 · 2022
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Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
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Raymond Li, Wen Xiao, Linzi Xing, Lanjun Wang, Gabriel Murray, and Giuseppe Carenini. 2022 · 2022
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A character-level length-control algorithm for non-autoregressive sentence summarization
Puyuan Liu, Xiang Zhang, and Lili Mou. 2022 · 2022
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Towards interpretable and efficient automatic reference-based summarization evaluation
Yixin Liu, Alexander Fabbri, Yilun Zhao, Pengfei Liu, Shafiq Joty, Chien-Sheng Wu, Caiming Xiong, and Dragomir Radev. 2023b · 2023
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Self-refine: Iterative refinement with self-feedback
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, and Peter Clark. 2023 · 2023
Explaining length bias in llm-based preference evaluations
Zhengyu Hu, Linxin Song, Jieyu Zhang, Zheyuan Xiao, Tianfu Wang, Zhengyu Chen, Nicholas Jing Yuan, Jianxun Lian, Kaize Ding, and Hui Xiong. 2024 · 2024
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Contranovo: A contrastive learning approach to enhance de novo peptide sequencing
Zhi Jin, Sheng Xu, Xiang Zhang, Tianze Ling, Nanqing Dong, Wanli Ouyang, Zhiqiang Gao, Cheng Chang, and Siqi Sun. 2024 · 2024
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Seam: A stochastic benchmark for multi-document tasks
Gili Lior, Avi Caciularu, Arie Cattan, Shahar Levy, Ori Shapira, and Gabriel Stanovsky. 2024 · 2024
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Benchmarking generation and evaluation capabilities of large language models for instruction controllable summarization
Yixin Liu, Alexander Fabbri, Jiawen Chen, Yilun Zhao, Simeng Han, Shafiq Joty, Pengfei Liu, Dragomir Radev, Chien-Sheng Wu, and Arman Cohan. 2024b · 2024
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Summarization is (almost) dead
Xiao Pu, Mingqi Gao, and Xiaojun Wan. 2023 · 2023
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, and Denny Zhou. 2023 · 2023
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React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2023 · 2023
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Ttida: Controllable generative data augmentation via text-to-text and text-to-image models
Yuwei Yin, Jean Kaddour, Xiang Zhang, Yixin Nie, Zhenguang Liu, Lingpeng Kong, and Qi Liu. 2023 · 2023
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Don‘t trust ChatGPT when your question is not in English: A study of multilingual abilities and types of LLMs
Xiang Zhang, Senyu Li, Bradley Hauer, Ning Shi, and Grzegorz Kondrak. 2023a · 2023
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Rishabh Agarwal, Avi Singh, Lei M. Zhang, Bernd Bohnet, Luis Rosias, Stephanie Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal Behbahani, Aleksandra Faust, and Hugo Larochelle. 2024 · 2024
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Physics of language models: Part 3.1, knowledge storage and extraction
Zeyuan Allen-Zhu and Yuanzhi Li. 2024 · 2024
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Lin Shi, Chiyu Ma, Wenhua Liang, Weicheng Ma, and Soroush Vosoughi. 2024 · 2024
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Scaling llm test-time compute optimally can be more effective than scaling model parameters
Charlie Snell, Jaehoon Lee, Kelvin Xu, and Aviral Kumar. 2024 · 2024
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Inference scaling flaws: The limits of llm resampling with imperfect verifiers
Benedikt Stroebl, Sayash Kapoor, and Arvind Narayanan. 2024 · 2024
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Toward self-improvement of llms via imagination, searching, and criticizing
Ye Tian, Baolin Peng, Linfeng Song, Lifeng Jin, Dian Yu, Haitao Mi, and Dong Yu. 2024 · 2024
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Adapted large language models can outperform medical experts in clinical text summarization
Dave Van Veen, Cara Van Uden, Louis Blankemeier, Jean-Benoit Delbrouck, Asad Aali, Christian Bluethgen, Anuj Pareek, Malgorzata Polacin, William Collins, Neera Ahuja, Curtis P. Langlotz, Jason Hom, Sergios Gatidis, John Pauly, and Akshay S. Chaudhari. 2024 · 2024
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Scaling inference computation: Compute-optimal inference for problem-solving with language models
Yangzhen Wu, Zhiqing Sun, Shanda Li, Sean Welleck, and Yiming Yang. 2024 · 2024
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Personalized abstractive summarization by tri-agent generation pipeline
Wen Xiao, Yujia Xie, Giuseppe Carenini, and Pengcheng He. 2024 · 2024
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Quiet-star: Language models can teach themselves to think before speaking
Eric Zelikman, Georges Harik, Yijia Shao, Varuna Jayasiri, Nick Haber, and Noah D. Goodman. 2024 · 2024
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Toolchain*: Efficient action space navigation in large language models with a* search
Yuchen Zhuang, Xiang Chen, Tong Yu, Saayan Mitra, Victor Bursztyn, Ryan A. Rossi, Somdeb Sarkhel, and Chao Zhang. 2024 · 2024
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Niklas Muennighoff, Zitong Yang, Weijia Shi, Xiang Lisa Li, Li Fei-Fei, Hannaneh Hajishirzi, Luke Zettlemoyer, Percy Liang, Emmanuel Candès, and Tatsunori Hashimoto. 2025 · 2025
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Learning to reason with llms
OpenAI. 2024 · 2025
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Sample, scrutinize and scale: Effective inference-time search by scaling verification
Eric Zhao, Pranjal Awasthi, and Sreenivas Gollapudi. 2025 · 2025
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