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cs.CL2026

Unveil: Unified Visual-Textual Integration and Distillation for Multi-modal Document Retrieval

Hao Sun, Yingyan Hou, Jiayan Guo +4

Document retrieval in real-world scenarios faces significant challenges due to diverse document formats and modalities. Traditional text-based approaches rely on tailored parsing t…

cs.CL2026

Retrieved In-Context Principles from Previous Mistakes

Hao Sun, Yong Jiang, Bo Wang +4

In-context learning (ICL) has been instrumental in adapting Large Language Models (LLMs) to downstream tasks using correct input-output examples. Recent advances have attempted to…

cs.CL2026

ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Hao Sun, Zile Qiao, Jiayan Guo +7

Effective information searching is essential for enhancing the reasoning and generation capabilities of large language models (LLMs). Recent research has explored using reinforceme…

cs.CL2024

Towards Verifiable Text Generation with Evolving Memory and Self-Reflection

Hao Sun, Hengyi Cai, Bo Wang +5

Despite the remarkable ability of large language models (LLMs) in language comprehension and generation, they often suffer from producing factually incorrect information, also know…

cs.CL2024

Boosting Disfluency Detection with Large Language Model as Disfluency Generator

Zhenrong Cheng, Jiayan Guo, Hao Sun +1

Current disfluency detection methods heavily rely on costly and scarce human-annotated data. To tackle this issue, some approaches employ heuristic or statistical features to gener…