Ep. 250 - May 31, 2024

ArXiv NLP research summaries for May 31, 2024. 00:20 FineRadScore: A Radiology Report Line-by-Line Evaluation Technique Generating Corrections with Severity Scores 01:37 Leveraging Large Language Models for Entity Matching 02:27 Reward-based Input Construction for Cross-document Relation Extraction 03:40 Passage-specific Prompt Tuning for Passage Reranking in Question Answering with Large Language Models 05:04 DORY: Deliberative Prompt Recovery for LLM 06:18 Unveiling the Lexical Sensitivity of LLMs: Combinatorial Optimization for Prompt Enhancement 07:35 It is Simple Sometimes: A Study On Improving Aspect-Based Sentiment Analysis Performance 08:59 FinGen: A Dataset for Argument Generation in Finance 09:42 Improving code-mixed hate detection by native sample mixing: A case study for Hindi-English code-mixed scenario 11:26 Multilingual Text Style Transfer: Datasets & Models for Indian Languages 13:01 An iterated learning model of language change that mixes supervised and unsupervised learning 14:01 Self-Augmented Preference Optimization: Off-Policy Paradigms for Language Model Alignment 15:29 That's Optional: A Contemporary Exploration of "that" Omission in English Subordinate Clauses 16:18 Don't Buy it! Reassessing the Ad Understanding Abilities of Contrastive Multimodal Models 17:20 Improving Reward Models with Synthetic Critiques 18:29 Towards Spoken Language Understanding via Multi-level Multi-grained Contrastive Learning 19:49 clembench-2024: A Challenging, Dynamic, Complementary, Multilingual Benchmark and Underlying Flexible Framework for LLMs as Multi-Action Agents 21:05 A comparison of correspondence analysis with PMI-based word embedding methods 22:05 Large Language Models: A New Approach for Privacy Policy Analysis at Scale 23:36 Preemptive Answer "Attacks" on Chain-of-Thought Reasoning 24:22 Learning to Estimate System Specifications in Linear Temporal Logic using Transformers and Mamba 25:48 OR-Bench: An Over-Refusal Benchmark for Large Language Models 27:20 Superlatives in Context: Explicit and Implicit Domain Restrictions for Superlative Frames 28:41 SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationales 30:33 Towards a Fluid computer 31:33 You Only Scan Once: Efficient Multi-dimension Sequential Modeling with LightNet 33:01 LACIE: Listener-Aware Finetuning for Confidence Calibration in Large Language Models 35:02 Direct Alignment of Language Models via Quality-Aware Self-Refinement 36:19 Code Pretraining Improves Entity Tracking Abilities of Language Models