Fetching the paper…
Reading the bibliography…
Learning chess strategies has been investigated widely, with most studies focussing on learning from previous games using search algorithms.
A coefficient of agreement for nominal scales
Cohen, J · 1960
Earlier work this paper cites.
Derivation of new readability formulas (automated readability index, fog count and flesch reading ease formula) for navy enlisted personnel
Kincaid, J. P., Fishburne Jr, R. P., Rogers, R. L. & Chissom, B. S · 1975
Earlier work this paper cites.
The measurement of observer agreement for categorical data
Landis, J. R. & Koch, G. G · 1977
Earlier work this paper cites.
The expert mind
Ross, P. E · 2006
Earlier work this paper cites.
Sentence and expression level annotation of opinions in user-generated discourse
Toprak, C., Jakob, N. & Gurevych, I · 2010
Earlier work this paper cites.
Learning to win by reading manuals in a monte-carlo framework
Branavan, S., Silver, D. & Barzilay, R · 2012
Earlier work this paper cites.
Glove: Global vectors for word representation
Pennington, J., Socher, R. & Manning, C. D · 2014
Earlier work this paper cites.
SemEval-2015 task 10: Sentiment analysis in Twitter
Rosenthal, S. et al · 2015
Earlier work this paper cites.
Deepchess: End-to-end deep neural network for automatic learning in chess
David, O. E., Netanyahu, N. S. & Wolf, L · 2016
Earlier work this paper cites.
Chess database
Schaigorodsky, A · 2016
Earlier work this paper cites.
Listen, attend, and walk: Neural mapping of navigational instructions to action sequences
Mei, H., Bansal, M. & Walter, M. R · 2016
Earlier work this paper cites.
A survey of event extraction methods from text for decision support systems
Hogenboom, F., Frasincar, F., Kaymak, U., De Jong, F. & Caron, E · 2016
Earlier work this paper cites.
A practical guide to sentiment annotation: Challenges and solutions
Mohammad, S · 2016
Earlier work this paper cites.
SQuAD: 100,000+ questions for machine comprehension of text
Rajpurkar, P., Zhang, J., Lopyrev, K. & Liang, P · 2016
Earlier work this paper cites.
Mastering chess and shogi by self-play with a general reinforcement learning algorithm
Silver, D. et al · 2017
Earlier work this paper cites.
Natural language grounding and grammar induction for robotic manipulation commands
Alomari, M., Duckworth, P., Hawasly, M., Hogg, D. C. & Cohn, A. G · 2017
Earlier work this paper cites.
Attention is all you need
Vaswani, A. et al · 2017
Earlier work this paper cites.
RACE: Large-scale ReAding comprehension dataset from examinations
Lai, G., Xie, Q., Liu, H., Yang, Y. & Hovy, E · 2017
Earlier work this paper cites.
An empirical comparison of model validation techniques for defect prediction models
Tantithamthavorn, C., McIntosh, S., Hassan, A. E. & Matsumoto, K · 2017
Cited alongside, same era.
Artificial intelligence and games , vol. 2 (Springer, 2018)
Yannakakis, G. N. & Togelius, J · 2018
Cited alongside, same era.
Extracting action sequences from texts based on deep reinforcement learning
Feng, W., Zhuo, H. H. & Kambhampati, S · 2018
Cited alongside, same era.
Learning to generate move-by-move commentary for chess games from large-scale social forum data
Jhamtani, H., Gangal, V., Hovy, E., Neubig, G. & Berg-Kirkpatrick, T · 2018
Cited alongside, same era.
GLUE: A multi-task benchmark and analysis platform for natural language understanding
Wang, A. et al · 2018
Cited alongside, same era.
Swag: A large-scale adversarial dataset for grounded commonsense inference
Roberta: A robustly optimized bert pretraining approach
Liu, Y. et al · 2019
Later among the works it cites.
Sentence-bert: Sentence embeddings using siamese bert-networks
Reimers, N. & Gurevych, I · 2019
Later among the works it cites.
Bert post-training for review reading comprehension and aspect-based sentiment analysis
Xu, H., Liu, B., Shu, L. & Philip, S. Y · 2019
Later among the works it cites.
Domain-level explainability–a challenge for creating trust in superhuman ai strategies
Andrulis, J., Meyer, O., Schott, G., Weinbach, S. & Gruhn, V · 2020
Later among the works it cites.
The wisdom of the gaming crowd
Jeffrey, R., Bian, P., Ji, F. & Sweetser, P · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Zellers, R., Bisk, Y., Schwartz, R. & Choi, Y · 2018
Cited alongside, same era.
Multimodal grounding for language processing
Beinborn, L., Botschen, T. & Gurevych, I · 2018
Cited alongside, same era.
Comparing knowledge-based reinforcement learning to neural networks in a strategy game
Nechepurenko, L., Voss, V. & Gritsenko, V · 2019
Cited alongside, same era.
Explainable agents and robots: Results from a systematic literature review
Anjomshoae, S., Najjar, A., Calvaresi, D. & Främling, K · 2019
Cited alongside, same era.
Sentimate: Learning to play chess through natural language processing
Kamlish, I., Chocron, I. B. & McCarthy, N · 2019
Cited alongside, same era.
Using unstructured data to improve the continuous planning of critical processes involving humans
Paterson, C., Calinescu, R., Manandhar, S. & Wang, D · 2019
Cited alongside, same era.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Sanh, V., Debut, L., Chaumond, J. & Wolf, T · 2019
Cited alongside, same era.
Noever, D., Ciolino, M. & Kalin, J · 2020
Later among the works it cites.
Bertscore: Evaluating text generation with BERT
Zhang, T., Kishore, V., Wu, F., Weinberger, K. Q. & Artzi, Y · 2020
Later among the works it cites.
BLEURT: Learning robust metrics for text generation
Sellam, T., Das, D. & Parikh, A · 2020
Later among the works it cites.
Albert: A lite bert for self-supervised learning of language representations
Lan, Z. et al · 2020
Later among the works it cites.
Fine-tuning pretrained language models: Weight initializations, data orders, and early stopping
Dodge, J. et al · 2020
Later among the works it cites.
An ensemble imbalanced classification method based on model dynamic selection driven by data partition hybrid sampling
Gao, X. et al · 2020
Later among the works it cites.
SentiBERT: A transferable transformer-based architecture for compositional sentiment semantics
Yin, D., Meng, T. & Chang, K.-W · 2020
Later among the works it cites.
Transformers: State-of-the-art natural language processing
Wolf, T. et al · 2020
Later among the works it cites.
Unleashing textual descriptions of business processes
Sànchez-Ferreres, J. et al · 2021
Later among the works it cites.
Watching a language model learning chess
Stöckl, A · 2021
Later among the works it cites.
Generating datasets with pretrained language models
Schick, T. & Schütze, H · 2021
Later among the works it cites.
Rafola: A rationale-annotated corpus for detecting indicators of forced labour
Guzman, E. M., Schlegel, V. & Batista-Navarro, R. T · 2022
Later among the works it cites.
Do you hear the people sing? key point analysis via iterative clustering and abstractive summarisation
Li, H., Schlegel, V., Batista-Navarro, R. & Nenadic, G · 2023
Closest in time.