Show newer

UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers. (arXiv:2301.13741v3 [cs.CV] UPDATED) 

Conversational Question Answering on Heterogeneous Sources. (arXiv:2204.11677v2 [cs.IR] UPDATED) 

Improving Gender Fairness of Pre-Trained Language Models without Catastrophic Forgetting. (arXiv:2110.05367v3 [cs.CL] UPDATED) 

SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs. (arXiv:2306.17842v1 [cs.CV]) 

Statler: State-Maintaining Language Models for Embodied Reasoning. (arXiv:2306.17840v1 [cs.RO]) 

Meta-Reasoning: Semantics-Symbol Deconstruction For Large Language Models. (arXiv:2306.17820v1 [cs.CL]) 

A Massive Scale Semantic Similarity Dataset of Historical English. (arXiv:2306.17810v1 [cs.CL]) 

Stay on topic with Classifier-Free Guidance. (arXiv:2306.17806v1 [cs.CL]) 

Towards Improving the Performance of Pre-Trained Speech Models for Low-Resource Languages Through Lateral Inhibition. (arXiv:2306.17792v1 [cs.CL]) 

Should you marginalize over possible tokenizations?. (arXiv:2306.17757v1 [cs.CL]) 

Token-Event-Role Structure-based Multi-Channel Document-Level Event Extraction. (arXiv:2306.17733v1 [cs.CL]) 

Improved NL2SQL based on Multi-layer Expert Network. (arXiv:2306.17727v1 [cs.CL]) 

Beyond Neural-on-Neural Approaches to Speaker Gender Protection. (arXiv:2306.17700v1 [eess.AS]) 

A New Task and Dataset on Detecting Attacks on Human Rights Defenders. (arXiv:2306.17695v1 [cs.CL]) 

X-RiSAWOZ: High-Quality End-to-End Multilingual Dialogue Datasets and Few-shot Agents. (arXiv:2306.17674v1 [cs.CL]) 

Biomedical Language Models are Robust to Sub-optimal Tokenization. (arXiv:2306.17649v1 [cs.CL]) 

Feature Representation Learning for NL2SQL Generation Based on Coupling and Decoupling. (arXiv:2306.17646v1 [cs.CL]) 

ChatGPT for Robotics: Design Principles and Model Abilities. (arXiv:2306.17582v1 [cs.AI]) 

Augmenting Holistic Review in University Admission using Natural Language Processing for Essays and Recommendation Letters. (arXiv:2306.17575v1 [cs.CL]) 

A Cost-aware Study of Depression Language on Social Media using Topic and Affect Contextualization. (arXiv:2306.17564v1 [cs.CL]) 

Show older
Qoto Mastodon

QOTO: Question Others to Teach Ourselves
An inclusive, Academic Freedom, instance
All cultures welcome.
Hate speech and harassment strictly forbidden.