12 papers
The Model Knows Another Way: Strategy Switching for Effective RLVR Exploration
Jin Cui, Xinyue Long, Boran Zhao +2
Reinforcement learning with verifiable rewards (RLVR) is often limited by insufficient exploration: difficult problems can yield uniformly incorrect rollout groups and therefore li…
StrataVLA: Hierarchical and Efficient 3D Geometric Grounding for Vision-Language-Action Models
Jin Cui, Zhaoyu Pu, Botao Cai +4
Vision-Language-Action (VLA) models inherit strong semantic priors from large-scale vision-language pretraining, yet remain limited in robotic manipulation by insufficient 3D spati…
Look Where It Matters: Adaptive Visual Refinement for Vision-Language-Action Models
Jin Cui, Yanbin Hu, Xinyue Long +3
Visual representations of VLA models remain unreliable for spatially precise robotic manipulation. We uncover that vision encoders in VLAs also exhibit attention artifacts previous…
HAFI-VLM: A Frequency Perspective for Diagnosing and Enhancing Visual Perception in Vision-Language Models
Jin Cui, Chuanchang Su, Jiayi Lu +3
Vision-language models (VLMs) remain unreliable when predictions require fine-grained visual evidence. We identify a previously overlooked cause: spectral response rigidity. Despit…
Distill What RGB Can Recover: Privileged 3D Evidence for RGB-Only Vision-Language Models
Yanbin Hu, Jin Cui, Jun Ye +4
3D scene understanding requires reasoning about entity existence, spatial layout, and object relations, yet RGB images alone often provide insufficient 3D cues. Existing 3D-VLMs co…
CAST: Collapse-Aware multi-Scale Topology Fusion for Multimodal Coreset Selection
Boran Zhao, Hetian Liu, Zhenxian Hu +3
The training of large multimodal models fundamentally relies on massive image-text datasets, which inevitably incur prohibitive computational overhead. Dataset selection offers a p…
ECHO: Continuous Hierarchical Memory for Vision-Language-Action Models
Yanbin Hu, Jin Cui, Jiayi Lu +6
Memory capacity is a critical factor determining the performance of Vision-Language-Action (VLA) models in long-horizon manipulation tasks. Existing memory-augmented architectures…
Retrieve, Integrate, and Synthesize: Spatial-Semantic Grounded Latent Visual Reasoning
Jin Cui, Xinyue Long, Xunyong Zhang +5
Multimodal Large Language Models (MLLMs) have made remarkable progress on vision-language reasoning, yet most methods still compress visual evidence into discrete textual thoughts,…
MIND: From Passive Mimicry to Active Reasoning through Capability-Aware Multi-Perspective CoT Distillation
Jin Cui, Jiaqi Guo, Jiepeng Zhou +6
While Large Language Models (LLMs) have emerged with remarkable capabilities in complex tasks through Chain-of-Thought reasoning, practical resource constraints have sparked intere…
"The Whole Is Greater Than the Sum of Its Parts": A Compatibility-Aware Multi-Teacher CoT Distillation Framework
Jin Cui, Jiaqi Guo, Ruixuan Yang +6
Chain-of-Thought (CoT) reasoning empowers Large Language Models (LLMs) with remarkable capabilities but typically requires prohibitive parameter scales. CoT distillation has emerge…
FAST: Topology-Aware Frequency-Domain Distribution Matching for Coreset Selection
Jin Cui, Boran Zhao, Jiajun Xu +3
Coreset selection compresses large datasets into compact, representative subsets, reducing the energy and computational burden of training deep neural networks. Existing methods ar…
MTLM: Incorporating Bidirectional Text Information to Enhance Language Model Training in Speech Recognition Systems
Qingliang Meng, Pengju Ren, Tian Li +2
Automatic speech recognition (ASR) systems normally consist of an acoustic model (AM) and a language model (LM). The acoustic model estimates the probability distribution of text g…