Title |
|---|
 In-Context Learning with Iterative Demonstration SelectionConference on Empirical Methods in Natural Language Processing (EMNLP), 2023 |
 Revisiting In-Context Learning with Long Context Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL), 2024 |
 Learning to Retrieve In-Context Examples for Large Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL), 2023 |
 A Survey on Evaluation of Large Language ModelsACM Transactions on Intelligent Systems and Technology (ACM TIST), 2023 Yu-Chu Chang Xu Wang Yongfeng Zhang Yuanyi Wu Linyi Yang ...Yue Zhang Yi-Ju Chang Philip S. Yu Qian Yang Xingxu Xie |
 Multi-Dimensional Evaluation of Text Summarization with In-Context
LearningAnnual Meeting of the Association for Computational Linguistics (ACL), 2023 |
 RECKONING: Reasoning through Dynamic Knowledge EncodingNeural Information Processing Systems (NeurIPS), 2023 |
 Compositional Exemplars for In-context LearningInternational Conference on Machine Learning (ICML), 2023 |
 Large Language Models Are Latent Variable Models: Explaining and Finding
Good Demonstrations for In-Context LearningNeural Information Processing Systems (NeurIPS), 2023 |
 In-context Examples Selection for Machine TranslationAnnual Meeting of the Association for Computational Linguistics (ACL), 2022 |
 Efficiently Scaling Transformer InferenceConference on Machine Learning and Systems (MLSys), 2022 |
 Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve ThemAnnual Meeting of the Association for Computational Linguistics (ACL), 2022 |
 Selective Annotation Makes Language Models Better Few-Shot LearnersInternational Conference on Learning Representations (ICLR), 2022 Hongjin Su Jungo Kasai Chen Henry Wu Weijia Shi Tianlu Wang ...Rui Zhang Mari Ostendorf Luke Zettlemoyer Noah A. Smith Tao Yu |
 Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsNeural Information Processing Systems (NeurIPS), 2022 |
 Fantastically Ordered Prompts and Where to Find Them: Overcoming
Few-Shot Prompt Order SensitivityAnnual Meeting of the Association for Computational Linguistics (ACL), 2021 |
 What Makes Good In-Context Examples for GPT-?Workshop on Knowledge Extraction and Integration for Deep Learning Architectures; Deep Learning Inside Out (DEELIO), 2021 |
 Graph Meta Learning via Local SubgraphsNeural Information Processing Systems (NeurIPS), 2020 |
 Language Models are Few-Shot LearnersNeural Information Processing Systems (NeurIPS), 2020 |
 GoEmotions: A Dataset of Fine-Grained EmotionsAnnual Meeting of the Association for Computational Linguistics (ACL), 2020 |
 Sentence-BERT: Sentence Embeddings using Siamese BERT-NetworksConference on Empirical Methods in Natural Language Processing (EMNLP), 2019 |
 Graph Attention NetworksInternational Conference on Learning Representations (ICLR), 2017 |
 Inductive Representation Learning on Large GraphsNeural Information Processing Systems (NeurIPS), 2017 |
