Papers
Detecting AI-Generated Content on Social Media with Multi-modal Language Models
Chenyang Yang, Shen Yan, Yibo Yang et al.
Calibrating LLM Judges: Linear Probes for Fast and Reliable Uncertainty Estimation
Bhaktipriya Radharapu, Eshika Saxena, Kenneth Li et al.
TaoType: Predicting Fine-Grained Typing Intent for Faster Search
Yipeng Yu, Yichen Yuan, Chengxiao Feng et al.
DocSplit: A Comprehensive Benchmark Dataset and Evaluation Approach for Document Packet Recognition and Splitting
Md Mofijul Islam, Md Sirajus Salekin, Nivedha Balakrishnan et al.
HAD: HAllucination Detection Language Models Based on a Comprehensive Hallucination Taxonomy
Fan Xu, Xinyu Hu, Zhenghan Yu et al.
R³A: Reinforced Reasoning for Relevance Assessment for RAG in User-Generated Content Platforms
Xiaowei Yuan, Lei Jin, Haoxin Zhang et al.
ARGUS: Policy-Adaptive Ad Governance via Evolving Reinforcement with Adversarial Umpiring
Deyi Ji, Junyu Lu, Xuanyi Liu et al.
TeachMaster: Generative Teaching via Code
Yuheng Wang, Runde Yang, Lin Wu et al.
Improving Hate Speech Detection by Fusing Textual and User Interaction Representations in Online Communities
Xu Gao, Dong Jing, Kee-hung Lai
Is Agentic RAG worth it? An experimental comparison of RAG approaches
Pietro Ferrazzi, Milica Cvjetićanin, Alessio Piraccini et al.
MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing
Junbo Niu, Zheng Liu, Zhuangcheng Gu et al.
Smarter, not Bigger: Fine-Tuned RAG-Enhanced LLMs for Automotive Hardware-in-the-Loop Testing
Chao Feng, Zihan Liu, Siddhant Gupta et al.
The Interplay between Metaphors and NLP
Joanne Boisson, Jose Camacho-Collados, Elisa Sanchez-Bayona et al.
Knowledge Control for Responsible Generative AI: Bridging Academia, Industry, and Society
Zheyuan Liu, Yixin Wan, Kai-Wei Chang et al.
Current Advances in LLM Reasoning
Akhil Arora, Vishrav Chaudhary, Julia Kreutzer et al.
Towards Effective and Efficient Multi-Agent Language Model Systems: Foundations, Prospects, and Applications
Xuan Wang, Shuxiang Cao, Yuchen Zhuang et al.
The Data Frontier for Large Language Models: Selection, Synthesis, and Tools
Lijun Wu, Wentao Zhang, Conghui He
Future of Work in the Age of LLMs
Zora Wang, Yijia Shao, David Nguyen et al.
One Task Vector is not Enough: A Large-Scale Study for In-Context Learning
Pavel Tikhonov, Ivan Oseledets, Elena Tutubalina
Continuous Context Sampling Allows Extending Diversity Boundaries of Large Language Models
Mateusz Bystroński, Doheon Han, Nitesh V. Chawla et al.
LLM as a Meta-Judge: Synthetic Data for NLP Evaluation Metric Validation
Lukáš Eigler, Jindřich Libovický, David Hurych
Optimizing Packing and Shuffling Strategies for Enhanced Performance in Generative Language Models
Yanbing Chen, Ruilin Wang, Zihao Yang et al.
CRL-Prompt: Contrastive and Reinforcement Learning for Soft Prompt Tuning for Text Classification
Danila Lapokin, Andrey Savchenko