works on

From the 1 of 71 linked papers with an AI index.

activity
20242026
most citedAdaptive Contrastive Learning on Multimodal Transformer for Review Helpfulness Predictions

6 citations · 6 across the 27 of their papers we have counts for

collaborators
Showing 2025Show all

23 papers · 1 filter

cs.CL2025

More Bias, Less Bias: BiasPrompting for Enhanced Multiple-Choice Question Answering

Duc Anh Vu, Thong Nguyen, Cong-Duy Nguyen +2

With the advancement of large language models (LLMs), their performance on multiple-choice question (MCQ) tasks has improved significantly. However, existing approaches face key li…

cs.DB2025

From Stimuli to Minds: Enhancing Psychological Reasoning in LLMs via Bilateral Reinforcement Learning

Yichao Feng, Haoran Luo, Lang Feng +2

Large Language Models show promise in emotion understanding, social reasoning, and empathy, yet they struggle with psychologically grounded tasks that require inferring implicit me…

cs.CR2025

P2P: A Poison-to-Poison Remedy for Reliable Backdoor Defense in LLMs

Shuai Zhao, Xinyi Wu, Shiqian Zhao +4

During fine-tuning, large language models (LLMs) are increasingly vulnerable to data-poisoning backdoor attacks, which compromise their reliability and trustworthiness. However, ex…

cs.CR2025

Rethinking Reasoning: A Survey on Reasoning-based Backdoors in LLMs

Man Hu, Xinyi Wu, Zuofeng Suo +5

With the rise of advanced reasoning capabilities, large language models (LLMs) are receiving increasing attention. However, although reasoning improves LLMs' performance on downstr…

cs.CL2025

GeoPQA: Bridging the Visual Perception Gap in MLLMs for Geometric Reasoning

Guizhen Chen, Weiwen Xu, Hao Zhang +4

Recent advancements in reinforcement learning (RL) have enhanced the reasoning abilities of large language models (LLMs), yet the impact on multimodal LLMs (MLLMs) is limited. Part…

cs.CL2025

Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

Yue Zhang, Yafu Li, Leyang Cui +13

While large language models (LLMs) have demonstrated remarkable capabilities across a range of downstream tasks, a significant concern revolves around their propensity to exhibit h…