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Qi Qian

ACL 2026×3ICLR 2026检索与知识强化学习与后训练智能体与工具对齐与偏好多模态
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方向广度13
合作网络9
0 一作 · 4 篇 · ACL 2026 / ICLR 2026

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2026 顶会论文

4
作者位次 #6/10ACL 2026Poster· Natural Language Processing

Controllable Memory Usage: Balancing Anchoring and Innovation in Long-Term Human–Agent Interaction

Zisu Huang · Muzhao Tian · Xiaohua Wang · Jingwen Xu · Zhengkang Guo · Qi Qian · Kaitao Song · Jiakang Yuan · Changze Lv · Xiaoqing Zheng

摘要

As LLM-based agents are increasingly used in long-term interactions, cumulative memory is critical for enabling personalization and maintaining stylistic consistency. However, most existing systems adopt an “all-or-nothing” approach to memory usage: incorporating all relevant past information can...

智能体与工具对齐与偏好检索与知识OpenReview 项目页
作者位次 #4/7ACL 2026Findings· Findings of ACL

Mitigating Hallucinations in VLM s: Enhancing Visual Attention via Head-Wise Perturbation

Zhenghua Wang · Yixin Wu · Feiran Zhang · Qi Qian · Changze Lv · Xuanjing Huang · Xiaoqing Zheng

摘要

Vision–Language Models (VLMs) have demonstrated strong capabilities in tasks that require joint understanding of text and images. However, as many VLMs are built upon pre-trained large language models, they often over-rely on linguistic priors at the expense of visual features, causing persistent...

多模态安全可解释性OpenReview 项目页
作者位次 #10/12ACL 2026Findings· Findings of ACL

Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling

Zhenghua Wang · Yiran Ding · Changze Lv · Yixin Wu · Tianlong Li · Zhibo Xu · Muling Wu · Tianyuan Shi · Shizheng Li · Qi Qian · Xuanjing Huang · Xiaoqing Zheng

摘要

Large Language Models (LLMs) still struggle with the “lost-in-the-middle” problem, where critical information located in the middle of long-context inputs is often underrepresented or lost. While existing methods attempt to address this by combining multi-scale rotary position embeddings (RoPE),...

效率与系统检索与知识长上下文与架构OpenReview 项目页

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