Title |
|---|
 Unifying Large Language Models and Knowledge Graphs: A RoadmapIEEE Transactions on Knowledge and Data Engineering (TKDE), 2023 |
 Judging LLM-as-a-Judge with MT-Bench and Chatbot ArenaNeural Information Processing Systems (NeurIPS), 2023 |
 Encouraging Divergent Thinking in Large Language Models through
Multi-Agent DebateConference on Empirical Methods in Natural Language Processing (EMNLP), 2023 |
 Improving Factuality and Reasoning in Language Models through Multiagent
DebateInternational Conference on Machine Learning (ICML), 2023 |
 Distilling Step-by-Step! Outperforming Larger Language Models with Less
Training Data and Smaller Model SizesAnnual Meeting of the Association for Computational Linguistics (ACL), 2023 Lokesh Nagalapatti Chun-Liang Li Chih-Kuan Yeh Hootan Nakhost Yasuhisa Fujii Alexander Ratner Ranjay Krishna Chen-Yu Lee Tomas Pfister |
 Do We Still Need Clinical Language Models?ACM Conference on Health, Inference, and Learning (CHIL), 2023 |
 Distilling Reasoning Capabilities into Smaller Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL), 2022 |
 How Large Language Models are Transforming Machine-Paraphrased
PlagiarismConference on Empirical Methods in Natural Language Processing (EMNLP), 2022 |
 Large Language Models are Zero-Shot ReasonersNeural Information Processing Systems (NeurIPS), 2022 |
 LinkBERT: Pretraining Language Models with Document LinksAnnual Meeting of the Association for Computational Linguistics (ACL), 2022 |
 A Benchmark Corpus for the Detection of Automatically Generated Text in
Academic PublicationsInternational Conference on Language Resources and Evaluation (LREC), 2022 |
 LoRA: Low-Rank Adaptation of Large Language ModelsInternational Conference on Learning Representations (ICLR), 2021 |
 Are Neural Language Models Good Plagiarists? A Benchmark for Neural
Paraphrase DetectionACM/IEEE Joint Conference on Digital Libraries (JCDL), 2021 |
 Explainable Automated Fact-Checking for Public Health ClaimsConference on Empirical Methods in Natural Language Processing (EMNLP), 2020 |
 Language Models are Few-Shot LearnersNeural Information Processing Systems (NeurIPS), 2020 |
 PyTorch: An Imperative Style, High-Performance Deep Learning LibraryNeural Information Processing Systems (NeurIPS), 2019 |
