Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving. (arXiv:2310.01957v2 [cs.RO] UPDATED)
(Dynamic) Prompting might be all you need to repair Compressed LLMs. (arXiv:2310.00867v2 [cs.CL] UPDATED)
Unlocking Bias Detection: Leveraging Transformer-Based Models for Content Analysis. (arXiv:2310.00347v2 [cs.CL] UPDATED)
HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language Models. (arXiv:2309.15701v2 [cs.CL] UPDATED)
A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future. (arXiv:2309.15402v2 [cs.CL] UPDATED)
Legal Question-Answering in the Indian Context: Efficacy, Challenges, and Potential of Modern AI Models. (arXiv:2309.14735v2 [cs.CL] UPDATED)
MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Models. (arXiv:2309.13567v2 [cs.CL] UPDATED)
ChatGPT v Bard v Bing v Claude 2 v Aria v human-expert. How good are AI chatbots at scientific writing?. (arXiv:2309.08636v3 [cs.CL] UPDATED)
Improving Code Generation by Dynamic Temperature Sampling. (arXiv:2309.02772v2 [cs.SE] UPDATED)
LMSanitator: Defending Prompt-Tuning Against Task-Agnostic Backdoors. (arXiv:2308.13904v2 [cs.CL] UPDATED)
RaLLe: A Framework for Developing and Evaluating Retrieval-Augmented Large Language Models. (arXiv:2308.10633v2 [cs.CL] UPDATED)
A Study on Robustness and Reliability of Large Language Model Code Generation. (arXiv:2308.10335v3 [cs.CL] UPDATED)
SummHelper: Collaborative Human-Computer Summarization. (arXiv:2308.08363v2 [cs.CL] UPDATED)
Thresh: A Unified, Customizable and Deployable Platform for Fine-Grained Text Evaluation. (arXiv:2308.06953v3 [cs.CL] UPDATED)
CLEVA: Chinese Language Models EVAluation Platform. (arXiv:2308.04813v2 [cs.CL] UPDATED)
SynJax: Structured Probability Distributions for JAX. (arXiv:2308.03291v3 [cs.LG] UPDATED)
Science and engineering for what? A large-scale analysis of students' projects in science fairs. (arXiv:2308.02962v2 [cs.AI] UPDATED)
Med-HALT: Medical Domain Hallucination Test for Large Language Models. (arXiv:2307.15343v2 [cs.CL] UPDATED)
Analysis of the Cambridge Multiple-Choice Questions Reading Dataset with a Focus on Candidate Response Distribution. (arXiv:2306.13047v4 [cs.CL] UPDATED)
Clickbait Detection via Large Language Models. (arXiv:2306.09597v2 [cs.CL] UPDATED)
All recent Computation and Language articles on arXiv.org for the Fediverse
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