Language Models are Causal Knowledge Extractors for Zero-shot Video Question Answering. (arXiv:2304.03754v1 [cs.CL])
Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models. (arXiv:2304.03738v1 [cs.CY])
Gated Mechanism Enhanced Multi-Task Learning for Dialog Routing. (arXiv:2304.03730v1 [cs.CL])
Interpretable Unified Language Checking. (arXiv:2304.03728v1 [cs.CL])
On the Importance of Contrastive Loss in Multimodal Learning. (arXiv:2304.03717v1 [cs.LG])
BenCoref: A Multi-Domain Dataset of Nominal Phrases and Pronominal Reference Annotations. (arXiv:2304.03682v1 [cs.CL])
Theoretical Conditions and Empirical Failure of Bracket Counting on Long Sequences with Linear Recurrent Networks. (arXiv:2304.03639v1 [cs.LG])
What does ChatGPT return about human values? Exploring value bias in ChatGPT using a descriptive value theory. (arXiv:2304.03612v1 [cs.CL])
Revisiting Automated Prompting: Are We Actually Doing Better?. (arXiv:2304.03609v1 [cs.CL])
ArmanTTS single-speaker Persian dataset. (arXiv:2304.03585v1 [cs.CL])
GEMINI: Controlling the Sentence-level Writing Style for Abstractive Text Summarization. (arXiv:2304.03548v1 [cs.CL])
InfoCTM: A Mutual Information Maximization Perspective of Cross-Lingual Topic Modeling. (arXiv:2304.03544v1 [cs.CL])
From Retrieval to Generation: Efficient and Effective Entity Set Expansion. (arXiv:2304.03531v1 [cs.CL])
SSS at SemEval-2023 Task 10: Explainable Detection of Online Sexism using Majority Voted Fine-Tuned Transformers. (arXiv:2304.03518v1 [cs.CL])
Hierarchical Catalogue Generation for Literature Review: A Benchmark. (arXiv:2304.03512v1 [cs.CL])
Linking Representations with Multimodal Contrastive Learning. (arXiv:2304.03464v1 [cs.CV])
Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4. (arXiv:2304.03439v1 [cs.CL])
Cleansing Jewel: A Neural Spelling Correction Model Built On Google OCR-ed Tibetan Manuscripts. (arXiv:2304.03427v1 [cs.CL])
Towards Corpus-Scale Discovery of Selection Biases in News Coverage: Comparing What Sources Say About Entities as a Start. (arXiv:2304.03414v1 [cs.CL])
CAPOT: Creating Robust Dense Query Encoders using Post Training Contrastive Alignment. (arXiv:2304.03401v1 [cs.IR])
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