activity
20222026
most citedThink-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph

55 citations · 64 across the 24 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CV2024

SURf: Teaching Large Vision-Language Models to Selectively Utilize Retrieved Information

Jiashuo Sun, Jihai Zhang, Yucheng Zhou +3

Large Vision-Language Models (LVLMs) have become pivotal at the intersection of computer vision and natural language processing. However, the full potential of LVLMs Retrieval-Augm…

cs.CV2024★ 1 cited

Look, Compare, Decide: Alleviating Hallucination in Large Vision-Language Models via Multi-View Multi-Path Reasoning

Xiaoye Qu, Jiashuo Sun, Wei Wei +1

Recently, Large Vision-Language Models (LVLMs) have demonstrated impressive capabilities in multi-modal context comprehension. However, they still suffer from hallucination problem…

cs.CL2024

ConflictBank: A Benchmark for Evaluating the Influence of Knowledge Conflicts in LLM

Zhaochen Su, Jun Zhang, Xiaoye Qu +6

Large language models (LLMs) have achieved impressive advancements across numerous disciplines, yet the critical issue of knowledge conflicts, a major source of hallucinations, has…

cs.CV2024★ 1 cited

Alleviating Hallucination in Large Vision-Language Models with Active Retrieval Augmentation

Xiaoye Qu, Qiyuan Chen, Wei Wei +2

Despite the remarkable ability of large vision-language models (LVLMs) in image comprehension, these models frequently generate plausible yet factually incorrect responses, a pheno…

cs.CL2024★ 2 cited

Ensuring Safe and High-Quality Outputs: A Guideline Library Approach for Language Models

Yi Luo, Zhenghao Lin, Yuhao Zhang +7

Large Language Models (LLMs) exhibit impressive capabilities but also present risks such as biased content generation and privacy issues. One of the current alignment techniques in…