Large Language Models

The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models ICLR 2024 The Earth is Flat because...: Investigating LLMs’ Belief towards Misinformation via Persuasive Conversation ACL 2024 The Effectiveness of LLMs as Annotators: A Comparative Overview and Empirical Analysis of Direct Representation COLING 2024 The Effect of Sampling Temperature on Problem Solving in Large Language Models EMNLP 2024 The Ethical Question – Use of Indigenous Corpora for Large Language Models COLING 2024 The Fine-Grained Complexity of Gradient Computation for Training Large Language Models NeurIPS 2024 The Fine-Tuning Paradox: Boosting Translation Quality Without Sacrificing LLM Abilities ACL 2024 The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale NeurIPS 2024 The Generation Gap: Exploring Age Bias in the Value Systems of Large Language Models EMNLP 2024 The Generative AI Paradox in Evaluation: “What It Can Solve, It May Not Evaluate” EACL 2024 The Hidden Space of Transformer Language Adapters ACL 2024 The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional Analysis ACL 2024 The Impact of Language on Arithmetic Proficiency: A Multilingual Investigation with Cross-Agent Checking Computation NAACL 2024 The Impact of Reasoning Step Length on Large Language Models ACL 2024 Themis: A Reference-free NLG Evaluation Language Model with Flexibility and Interpretability EMNLP 2024 The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm EMNLP 2024 The Music Maestro or The Musically Challenged, A Massive Music Evaluation Benchmark for Large Language Models ACL 2024 The Overlooked Repetitive Lengthening Form in Sentiment Analysis EMNLP 2024 The Paradox of Preference: A Study on LLM Alignment Algorithms and Data Acquisition Methods NAACL 2024 The ParlaSent Multilingual Training Dataset for Sentiment Identification in Parliamentary Proceedings COLING 2024 The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models NeurIPS 2024 The Probabilities Also Matter: A More Faithful Metric for Faithfulness of Free-Text Explanations in Large Language Models ACL 2024 The Promises and Pitfalls of Using Language Models to Measure Instruction Quality in Education NAACL 2024 The Reasonableness Behind Unreasonable Translation Capability of Large Language Model ICLR 2024 The Representation Landscape of Few-Shot Learning and Fine-Tuning in Large Language Models NeurIPS 2024