5 papers
Uni-LaDiR: Latent Diffusion Unifies Multimodal Reasoning
Haoqiang Kang, Yizhe Zhang, Nikki Lijing Kuang +3
Multimodal models increasingly think with different modalities such as images, 3D point clouds, and robot states, not just text. Yet each modality is still encoded into its own rep…
LaDi-RL: Latent Diffusion Reasoning Prevents Entropy Collapse in Reinforcement Learning
Haoqiang Kang, Yizhe Zhang, Nikki Lijing Kuang +2
Reinforcement learning has become a central paradigm for improving LLM reasoning, but most existing methods optimize policies over discrete token sequences. This creates a mismatch…
LaDiR: Latent Diffusion Enhances LLMs for Text Reasoning
Haoqiang Kang, Yizhe Zhang, Nikki Lijing Kuang +4
Large Language Models (LLMs) demonstrate their reasoning ability through chain-of-thought (CoT) generation. However, LLM's autoregressive decoding may limit the ability to revisit…
WebUIBench: A Comprehensive Benchmark for Evaluating Multimodal Large Language Models in WebUI-to-Code
Zhiyu Lin, Zhengda Zhou, Zhiyuan Zhao +4
With the rapid advancement of Generative AI technology, Multimodal Large Language Models(MLLMs) have the potential to act as AI software engineers capable of executing complex web…
Log-concave Sampling from a Convex Body with a Barrier: a Robust and Unified Dikin Walk
Yuzhou Gu, Nikki Lijing Kuang, Yi-An Ma +2
We consider the problem of sampling from a -dimensional log-concave distribution for -Lipschitz , constrained to a convex body with an efficient…