7 papers
Understanding NVIDIA Grace-Blackwell Unified Memory Through Placement-Controlled Microbenchmarks
Nathan Graddon, Aaron Jarmusch, Sunita Chandrasekaran
NVIDIA Grace--Blackwell systems make CPU--GPU memory increasingly unified at the programming level, but unified addressability does not make the memory system uniform. A CUDA manag…
MeSD: Multi-Evidence Self-Distillation for VideoLLM
Weijie Zhu, Han Fang, Hanyu Fu +13
While reinforcement learning with verifiable rewards provides reliable outcome supervision for VideoLLMs, sequence-level rewards offer limited token-level guidance. On-policy self-…
GeoAnchor: Collaborative Reasoning via Latent Decomposition for 3D Spatial Understanding
Hao Li, Han Fang, Zixin Pan +8
Although multimodal large language models (MLLMs) have achieved remarkable progress, understanding 3D spatial relationships from 2D images remains a critical challenge. Existing me…
Mixture-of-Thought-Tokens: Unifying Perception and Reasoning for Free-form Multimodal Grounding
Tianyi Gao, Han Fang, Tianyi Ding +9
Multimodal Large Language Models have made great progress in grounding tasks, yet existing methods still struggle to unify precise localization and complex reasoning. For one thing…
ProtRLSearch: A Multi-Round Multimodal Protein Search Agent with Large Language Models Trained via Reinforcement Learning
Congying Liu, Taihao Li, Ming Huang +5
Protein analysis tasks arising in healthcare settings often require accurate reasoning under protein sequence constraints, involving tasks such as functional interpretation of dise…
RefBench-PRO: Perceptual and Reasoning Oriented Benchmark for Referring Expression Comprehension
Tianyi Gao, Hao Li, Han Fang +8
Referring Expression Comprehension (REC) is a vision-language task that localizes a specific image region based on a textual description. Existing REC benchmarks primarily evaluate…
TSPO: Temporal Sampling Policy Optimization for Long-form Video Language Understanding
Canhui Tang, Zifan Han, Hongbo Sun +7
Multimodal Large Language Models (MLLMs) have demonstrated significant progress in vision-language tasks, yet they still face challenges when processing long-duration video inputs.…