Papers by Yuhong Chen

3 papers
ECLM: Entity Level Language Model for Spoken Language Understanding with Chain of Intent (2025.acl-long)

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Challenge: Large Language Models (LLMs) have demonstrated impressive capabilities in language generation and general task performance, but their application to spoken language understanding remains challenging.
Approach: They propose an Entity-level Language Model framework which reformulates slot-filling as an entity recognition task and introduces a new concept, Chain of Intent, to enable step-by-step multi-intent recognition.
Outcome: The proposed framework outperforms strong baselines such as Uni-MIS and achieves gains of 3.7% and 3.1% on MixATIS and MixSNIPS.
SWE-AGILE: A Software Agent Framework for Efficiently Managing Dynamic Reasoning Context (2026.findings-acl)

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Challenge: representative ReAct-style approaches lack explicit System-2 reasoning for deep analysis and handling complex edge cases.
Approach: They propose a software agent framework that preserves full reasoning history while compressing historical reasoning content into concise Reasoning Digests.
Outcome: Empirically, the proposed framework sets a new standard for 7B-8B models on SWE-Bench-Verified using only 2.2k trajectories and 896 tasks.
DMIN: A Discourse-specific Multi-granularity Integration Network for Conversational Aspect-based Sentiment Quadruple Analysis (2024.findings-acl)

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Challenge: Existing studies focus on enhancing token-level interactions, but lack sufficient modeling of discourse structure information.
Approach: They propose to use a discourse structure called "thread" to enhance token interaction among different utterances.
Outcome: The proposed model achieves state-of-the-art on two datasets.

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