You don't need a personality test to know these models are unreliable: Assessing the Reliability of Large Language Models on Psychometric Instruments. (arXiv:2311.09718v1 [cs.CL])
Regularized Conventions: Equilibrium Computation as a Model of Pragmatic Reasoning. (arXiv:2311.09712v1 [cs.CL])
Large Language Model Inference with Lexical Shortlisting. (arXiv:2311.09709v1 [cs.CL])
A Self-enhancement Multitask Framework for Unsupervised Aspect Category Detection. (arXiv:2311.09708v1 [cs.CL])
GenCodeSearchNet: A Benchmark Test Suite for Evaluating Generalization in Programming Language Understanding. (arXiv:2311.09707v1 [cs.CL])
Deceiving Semantic Shortcuts on Reasoning Chains: How Far Can Models Go without Hallucination?. (arXiv:2311.09702v1 [cs.CL])
Fumbling in Babel: An Investigation into ChatGPT's Language Identification Ability. (arXiv:2311.09696v1 [cs.CL])
Whispers of Doubt Amidst Echoes of Triumph in NLP Robustness. (arXiv:2311.09694v1 [cs.CL])
BLT: Can Large Language Models Handle Basic Legal Text?. (arXiv:2311.09693v1 [cs.CL])
Inducing Political Bias Allows Language Models Anticipate Partisan Reactions to Controversies. (arXiv:2311.09687v1 [cs.CL])
Do Physicians Know How to Prompt? The Need for Automatic Prompt Optimization Help in Clinical Note Generation. (arXiv:2311.09684v1 [cs.CL])
MacGyver: Are Large Language Models Creative Problem Solvers?. (arXiv:2311.09682v1 [cs.CL])
R-Tuning: Teaching Large Language Models to Refuse Unknown Questions. (arXiv:2311.09677v1 [cs.CL])
Where Do People Tell Stories Online? Story Detection Across Online Communities. (arXiv:2311.09675v1 [cs.CL])
Improving the Generation Quality of Watermarked Large Language Models via Word Importance Scoring. (arXiv:2311.09668v1 [cs.CL])
Evaluating LLM Agent Group Dynamics against Human Group Dynamics: A Case Study on Wisdom of Partisan Crowds. (arXiv:2311.09665v1 [cs.CL])
Evolving Domain Adaptation of Pretrained Language Models for Text Classification. (arXiv:2311.09661v1 [cs.CL])
Structured Chemistry Reasoning with Large Language Models. (arXiv:2311.09656v1 [cs.CL])
ICXML: An In-Context Learning Framework for Zero-Shot Extreme Multi-Label Classification. (arXiv:2311.09649v1 [cs.LG])
Event Causality Is Key to Computational Story Understanding. (arXiv:2311.09648v1 [cs.CL])
All recent Computation and Language articles on arXiv.org for the Fediverse
Inspired by https://twitter.com/arxiv_cscl