5 papers · 1 filter
Document Summarization with Conformal Importance Guarantees
Bruce Kuwahara, Chen-Yuan Lin, Xiao Shi Huang +5
Automatic summarization systems have advanced rapidly with large language models (LLMs), yet they still lack reliable guarantees on inclusion of critical content in high-stakes dom…
Resisting Contextual Interference in RAG via Parametric-Knowledge Reinforcement
Chenyu Lin, Yilin Wen, Du Su +5
Retrieval-augmented generation (RAG) improves performance on knowledge-intensive tasks but can be derailed by wrong, irrelevant, or conflicting retrieved text, causing models to re…
HiCaM: A Hierarchical-Causal Modification Framework for Long-Form Text Modification
Yuntao Shi, Yi Luo, Yeyun Gong +1
Large Language Models (LLMs) have achieved remarkable success in various domains. However, when handling long-form text modification tasks, they still face two major problems: (1)…
Generalized Category Discovery in Event-Centric Contexts: Latent Pattern Mining with LLMs
Yi Luo, Qiwen Wang, Junqi Yang +5
Generalized Category Discovery (GCD) aims to classify both known and novel categories using partially labeled data that contains only known classes. Despite achieving strong perfor…
DeepThink: Aligning Language Models with Domain-Specific User Intents
Yang Li, Mingxuan Luo, Yeyun Gong +4
Supervised fine-tuning with synthesized instructions has been a common practice for adapting LLMs to domain-specific QA tasks. However, the synthesized instructions deviate from re…