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20242026
most citedEvaluating Conversational Recommender Systems via Large Language Models: A User-Centric Framework

3 citations · 7 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024

GEMeX: A Large-Scale, Groundable, and Explainable Medical VQA Benchmark for Chest X-ray Diagnosis

Bo Liu, Ke Zou, Liming Zhan +7

Medical Visual Question Answering (Med-VQA) combines computer vision and natural language processing to automatically answer clinical inquiries about medical images. However, curre…

cs.CL2024★ 3 cited

AI Can Be Cognitively Biased: An Exploratory Study on Threshold Priming in LLM-Based Batch Relevance Assessment

Nuo Chen, Jiqun Liu, Xiaoyu Dong +3

Cognitive biases are systematic deviations in thinking that lead to irrational judgments and problematic decision-making, extensively studied across various fields. Recently, large…

cs.CL2024

Understanding Layer Significance in LLM Alignment

Guangyuan Shi, Zexin Lu, Xiaoyu Dong +4

Aligning large language models (LLMs) through supervised fine-tuning is essential for tailoring them to specific applications. Recent studies suggest that alignment primarily adjus…

cs.CL2024

Continual Dialogue State Tracking via Reason-of-Select Distillation

Yujie Feng, Bo Liu, Xiaoyu Dong +4

An ideal dialogue system requires continuous skill acquisition and adaptation to new tasks while retaining prior knowledge. Dialogue State Tracking (DST), vital in these systems, o…

cs.IR2024★ 1 cited

Vector Quantization for Recommender Systems: A Review and Outlook

Qijiong Liu, Xiaoyu Dong, Jiaren Xiao +6

Vector quantization, renowned for its unparalleled feature compression capabilities, has been a prominent topic in signal processing and machine learning research for several decad…