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Heng Dong

ACL 2026×2ICML 2026推理强化学习与后训练效率与系统多模态评测与基准
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0 一作 · 3 篇 · ACL 2026 / ICML 2026

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2026 顶会论文

3
作者位次 #6/9ACL 2026Poster· Natural Language Processing

Learning from Mistakes: Negative Reasoning Samples Enhance Out-of-Domain Generalization

Tian Xueyun · MingHua Ma · Bingbing Xu · Nuoyan Lyu · Wei Li · Heng Dong · Zheng Chu · Yuanzhuo Wang · Huawei Shen

摘要

Supervised fine-tuning (SFT) on chain-of-thought (CoT) trajectories demonstrations is a common approach for enabling reasoning in large language models. Standard practices typically only retain trajectories with correct final answers ( positives ) while ignoring the rest ( negatives ). We argue t...

推理强化学习与后训练效率与系统OpenReview 项目页
作者位次 #4/6ACL 2026Findings· Findings of ACL

ROMA : Real-time Omni-Multimodal Assistant with Interactive Streaming Understanding

Tian Xueyun · Wei Li · Bingbing Xu · Heng Dong · Yuanzhuo Wang · Huawei Shen

摘要

Recent Omni-multimodal Large Language Models show promise in unified audio, vision, and text modeling. However, streaming audio-video understanding remains challenging, as existing approaches suffer from disjointed capabilities: they typically exhibit incomplete modality support or lack autonomou...

多模态评测与基准对齐与偏好OpenReview 项目页

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