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Let's Think Frame by Frame with VIP: A Video Infilling and Prediction Dataset for Evaluating Video Chain-of-Thought. (arXiv:2305.13903v3 [cs.CL] UPDATED) 

Leveraging Human Feedback to Scale Educational Datasets: Combining Crowdworkers and Comparative Judgement. (arXiv:2305.12894v2 [cs.CL] UPDATED) 

Sabi\'a: Portuguese Large Language Models. (arXiv:2304.07880v4 [cs.CL] UPDATED) 

MLRegTest: A Benchmark for the Machine Learning of Regular Languages. (arXiv:2304.07687v2 [cs.LG] UPDATED) 

A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity. (arXiv:2302.04023v3 [cs.CL] UPDATED) 

idT5: Indonesian Version of Multilingual T5 Transformer. (arXiv:2302.00856v2 [cs.CL] UPDATED) 

Vicarious Offense and Noise Audit of Offensive Speech Classifiers: Unifying Human and Machine Disagreement on What is Offensive. (arXiv:2301.12534v4 [cs.CL] UPDATED) 

Interpreting Embedding Spaces by Conceptualization. (arXiv:2209.00445v3 [cs.CL] UPDATED) 

An Attention-Based Model for Predicting Contextual Informativeness and Curriculum Learning Applications. (arXiv:2204.09885v2 [cs.CL] UPDATED) 

Quantifying Gender Bias Towards Politicians in Cross-Lingual Language Models. (arXiv:2104.07505v2 [cs.CL] UPDATED) 

Learning From How Humans Correct. (arXiv:2102.00225v15 [cs.CL] UPDATED) 

FigStep: Jailbreaking Large Vision-language Models via Typographic Visual Prompts. (arXiv:2311.05608v1 [cs.CR]) 

FAMuS: Frames Across Multiple Sources. (arXiv:2311.05601v1 [cs.CL]) 

Accuracy of a Vision-Language Model on Challenging Medical Cases. (arXiv:2311.05591v1 [cs.CV]) 

Zero-Shot Goal-Directed Dialogue via RL on Imagined Conversations. (arXiv:2311.05584v1 [cs.LG]) 

Removing RLHF Protections in GPT-4 via Fine-Tuning. (arXiv:2311.05553v1 [cs.CL]) 

The Iron(ic) Melting Pot: Reviewing Human Evaluation in Humour, Irony and Sarcasm Generation. (arXiv:2311.05552v1 [cs.CL]) 

Towards End-to-End Spoken Grammatical Error Correction. (arXiv:2311.05550v1 [cs.CL]) 

Text Representation Distillation via Information Bottleneck Principle. (arXiv:2311.05472v1 [cs.CL]) 

All Should Be Equal in the Eyes of Language Models: Counterfactually Aware Fair Text Generation. (arXiv:2311.05451v1 [cs.CL]) 

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