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Hui Liu

ICLR 2026×6ACL 2026×4AAAI 2026CVPR 2026多模态智能体与工具推理对齐与偏好效率与系统
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0 一作 · 12 篇 · ICLR 2026 / ACL 2026 / AAAI 2026 / CVPR 2026

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2026 顶会论文

12
作者位次 #7/8ACL 2026Poster· Natural Language Processing

Anchoring the Cache: Mitigating Contextual Hallucination in KV -Compressed Long-Context Summarization

Yu Fu · Chen Luo · Josef Valvoda · Xin Zhang · Xuejing Lei · Xiao Pan · Hui Liu · Yue Dong

摘要

Key-Value (KV) cache compression techniques have improved the efficiency of long-context summarization in Large Language Models (LLMs), but their impact on model hallucination remains underexplored. In this paper, we present the first systematic study of how KV cache compression affects hallucina...

效率与系统安全数据与预训练OpenReview 项目页
作者位次 #5/12ACL 2026Findings· Findings of ACL

A Reward-Guided Dual-Phase Framework for Adaptive Inference-Time Reasoning

Yingqian Cui · Zhenwei Dai · Pengfei He · Bing He · Hui Liu · Zhan Shi · Xianfeng Tang · Jingying Zeng · Suhang Wang · Yue Xing · Jiliang Tang · Benoit Dumoulin

摘要

Large Language Models (LLMs) have made strong progress in reasoning. To enhance the reasoning performance, a common inference-time approach is tree-based search, which decomposes the reasoning process into multiple steps, expands multiple reasoning paths, and uses reward models to prune and selec...

推理效率与系统对齐与偏好OpenReview 项目页
作者位次 #9/14ACL 2026Findings· Findings of ACL

Graph-Assisted Large Language Models: A Perspective on Mitigating Intrinsic Limitations

Haitong Luo · Fali Wang · Weiyao Zhang · Xianren Zhang · Zhiwei Zhang · Tianxiang Zhao · Minhua Lin · Jiahao Zhang · Hui Liu · Xianfeng Tang · Qi He · Suhang Wang · Xuying Meng · Yujun Zhang

摘要

Large language models (LLMs) have made progress in knowledge-intensive tasks, reasoning and planning, and collaborative problem solving, yet they exhibit intrinsic limitations such as knowledge cutoff, single-threaded reasoning that hinders finer-grained branch and aggregation, and rigid collabor...

推理智能体与工具可解释性OpenReview 项目页
作者位次 #7/12ACL 2026Findings· Findings of ACL

Do VLM s Have a Moral Backbone? A Study on the Fragile Morality of Vision-Language Models

Zhining Liu · Tianyi Wang · Xiao Lin · Penghao Ouyang · Gaotang Li · Ze Yang · Hui Liu · Sumit Keswani · Vishwa Pardeshi · Huijun Zhao · Wei Fan · Hanghang Tong

摘要

Despite substantial efforts toward improving the moral alignment of Vision-Language Models (VLMs), it remains unclear whether their ethical judgments are stable in realistic settings. This work studies moral robustness in VLMs, defined as the ability to preserve moral judgments under textual and...

多模态社会与人本对齐与偏好OpenReview 项目页

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