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Qifei Zhang

ACL 2026×3对齐与偏好多模态检索与知识推理效率与系统
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0 一作 · 3 篇 · ACL 2026

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2026 顶会论文

3
作者位次 #5/7ACL 2026Poster· Natural Language Processing

C o G : Controllable Graph Reasoning via Relational Blueprints and Failure-Aware Refinement over Knowledge Graphs

Yuanxiang Liu · Songze Li · Xiaoke Guo · Zhaoyan Gong · Qifei Zhang · Huajun Chen · Wen Zhang

摘要

Large Language Models (LLMs) have demonstrated remarkable reasoning capabilities but often grapple with reliability challenges like hallucinations. While Knowledge Graphs (KGs) offer explicit grounding, existing paradigms of KG-augmented LLMs typically exhibit cognitive rigidity—applying homogene...

检索与知识推理对齐与偏好OpenReview 项目页
作者位次 #4/8ACL 2026Poster· Natural Language Processing

SAME : Signer-Aware Mixture-of-Experts for Test-Time Adaptation in Sign Language Translation

Lujia Yang · Weicai Yan · Yongbo He · Qifei Zhang · Tao Jin · Jinshan Zhang · Meng Xi · Jianwei Yin

摘要

Sign language translation (SLT) is essential for bridging communication between the deaf and hearing communities, but real-world deployment suffers from domain shift such as signer variability, lighting, and background changes. Supervised fine-tuning is impractical due to limited labeled data, an...

效率与系统对齐与偏好多模态OpenReview 项目页
作者位次 #9/9ACL 2026Findings· Findings of ACL

Generative-to-Discriminative Test-Time Adaptation via Manifold-Aware Diffusion and B ayesian Distillation

Boyun Zhang · Zequn Xie · Fangming Feng · Zihan Zhang · Yongbo He · Chuxin Wang · Sihang Cai · Tao Jin · Qifei Zhang

摘要

Multimodal Sentiment Analysis (MSA) models typically suffer significant performance degradation under domain shifts. While Test-Time Adaptation (TTA) aims to mitigate this, existing discriminative approaches often succumb to “confident but wrong” predictions on out-of-distribution samples. Conver...

安全多模态强化学习与后训练OpenReview 项目页

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