4 papers · 1 filter
Se-DPO: Self-Evolving Token Credit for Direct Preference Optimization
Wenxiao Zhao, Shu Wang, Ying Nian Wu
Direct Preference Optimization (DPO) aggregates token-level log-probability ratios via uniform summation, implicitly treating all tokens as contributing equally to the preference s…
Children's Intelligence Tests Pose Challenges for MLLMs? KidGym: A 2D Grid-Based Reasoning Benchmark for MLLMs
Hengwei Ye, Yuanting Guan, Yuxuan Ge +7
Multimodal Large Language Models (MLLMs) combine the linguistic strengths of LLMs with the ability to process multimodal data, enbaling them to address a broader range of visual ta…
Latent Thought Models with Variational Bayes Inference-Time Computation
Deqian Kong, Minglu Zhao, Dehong Xu +8
We propose a novel class of language models, Latent Thought Models (LTMs), which incorporate explicit latent thought vectors that follow an explicit prior model in latent space. Th…
Explore the Reasoning Capability of LLMs in the Chess Testbed
Shu Wang, Lei Ji, Renxi Wang +4
Reasoning is a central capability of human intelligence. In recent years, with the advent of large-scale datasets, pretrained large language models have emerged with new capabiliti…