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20232026
most citedWorldValuesBench: A Large-Scale Benchmark Dataset for Multi-Cultural Value Awareness of Language Models

2 citations · 5 across the 21 of their papers we have counts for

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11 papers · 1 filter

cs.CL2026

PVFH-Bench: Benchmarking Premise-Induced Visual Fixation Hallucinations in Vision-Language Models

Xinhao Wang, Junbo Cui, Zhenghao Liu +4

Large Vision-Language Models (LVLMs) have achieved remarkable progress across a wide range of multimodal tasks. However, object hallucination remains a persistent challenge, underm…

cs.CL2026

REFACT: Adaptive Fact Restatement for Compact and Faithful Chain-of-Thought Reasoning

Zhensheng Jin, Xin Dai, Zhenghao Liu +5

Large Language Models (LLMs) increasingly leverage long-form reasoning to solve complex tasks, yet their reasoning processes can deviate from the provided context when evidence is…

cs.CL2026

SPARK: Adaptive Parametric Knowledge Participation for Faithful Retrieval-Augmented Generation

Ruochang Li, Pengcheng Huang, Zhenghao Liu +5

Retrieval-augmented generation (RAG) enhances the faithfulness of large language models (LLMs) by incorporating external knowledge into the generation process. However, conflicts b…

cs.IR2026

Memory Shot for Long-Term Dialogue

Chunyi Peng, Haidong Xin, Xuanshuo Sheng +7

Large Language Models (LLMs) have demonstrated strong capabilities in general conversation, instruction following, and complex reasoning. However, in long-term dialogue settings, t…

cs.IR2026

ReAlign: Optimizing the Visual Document Retriever with Reasoning-Guided Fine-Grained Alignment

Hao Yang, Yifan Ji, Zhipeng Xu +6

Visual document retrieval aims to retrieve a set of document pages relevant to a query from visually rich collections. Existing methods often employ Vision-Language Models (VLMs) t…

cs.AI2026

Lang2Act: Fine-Grained Visual Reasoning through Self-Emergent Linguistic Toolchains

Yuqi Xiong, Chunyi Peng, Zhipeng Xu +6

Visual Retrieval-Augmented Generation (VRAG) enhances Vision-Language Models (VLMs) by incorporating external visual documents to address a given query. Existing VRAG frameworks us…

cs.CL2026

MetaMem: Evolving Meta-Memory for Knowledge Utilization through Self-Reflective Symbolic Optimization

Haidong Xin, Xinze Li, Zhenghao Liu +6

Existing memory systems enable Large Language Models (LLMs) to support long-horizon human-LLM interactions by persisting historical interactions beyond limited context windows. How…

cs.CV2026

UNIKIE-BENCH: Benchmarking Large Multimodal Models for Key Information Extraction in Visual Documents

Yifan Ji, Zhipeng Xu, Zhenghao Liu +7

Key Information Extraction (KIE) from real-world documents remains challenging due to substantial variations in layout structures, visual quality, and task-specific information req…

cs.SE2026

Teaching LLMs to Learn Tool Trialing and Execution through Environment Interaction

Xingjie Gao, Pengcheng Huang, Zhenghao Liu +6

Equipping Large Language Models (LLMs) with external tools enables them to solve complex real-world problems. However, the robustness of existing methods remains a critical challen…

cs.CL2026

Long-Chain Reasoning Distillation via Adaptive Prefix Alignment

Zhenghao Liu, Zhuoyang Wu, Xinze Li +6

Large Language Models (LLMs) have demonstrated remarkable reasoning capabilities, particularly in solving complex mathematical problems. Recent studies show that distilling long re…

cs.LG2026

Revealing the Attention Floating Mechanism in Masked Diffusion Models

Xin Dai, Pengcheng Huang, Zhenghao Liu +6

Masked diffusion models (MDMs), which leverage bidirectional attention and a denoising process, are narrowing the performance gap with autoregressive models (ARMs). However, their…