3 citations · 17 across the 60 of their papers we have counts for
69 papers
RSIPO: Recursive Self-Improving Policy Optimization for Agentic Reinforcement Learning via Skill-Policy Co-Evolution
Fan Zhang, Hao Wu, Jinyang Wu +7
Recent focus in agentic reinforcement learning (RL) seeks to improve credit assignment in long-horizon tasks. One promising direction combines reinforcement learning with verifiabl…
MedZERO: Self-Evolving Agents for Open-Ended Medical Reasoning Through Controlled Knowledge Accumulation
Xilin Dang, Weilin Ruan, Xue Yang +4
Large language models (LLMs) have shown promise in medical question answering and clinical reasoning, yet their improvement remains constrained by static parametric knowledge and c…
ThinkV2V: Unleashing the Reasoning Capability of MLLMs for Instruction-Guided Video Editing
Donghao Zhou, Haoyang He, Fan Zhang +10
Instruction-guided video editing has made significant progress, yet existing methods use multimodal large language models (MLLMs) primarily as semantic encoders, so they often fall…
Noisy Test-Time Reinforcement Learning for Code LLMs
Xikai Yang, Hieu Trung Nguyen, Dunyuan Xu +4
Large language models (LLMs) have demonstrated remarkable performance across various code-related tasks. However, unlike carefully curated datasets that are typically high-quality…
PackLab: A Comprehensive Framework for Developing, Training, and Evaluating MLLMs in Robotic Bin Packing
Donghao Zhou, Jia-Hui Pan, Fan Zhang +6
Robotic bin packing requires long-horizon sequential decision-making, as each object placement affects the available space for subsequent packing. Existing methods primarily rely o…
JEPA-Anything: Learning Predictive Models across Different Worlds
Taoyong Cui, Zhongyao Wang, Xinyue Xu +10
World modeling enables intelligence to anticipate consequences, guide interventions, and learn from interaction. Yet predictive models remain domain-specific: can a common learning…
Orthogonal JEPA: Factorized Predictive States for Latent World Models
Taoyong Cui, Pheng Ann Heng, Wanli Ouyang
World models construct latent states that support prediction, planning, and reasoning about an underlying system. Joint-embedding predictive architectures (JEPAs) offer a direct wa…
VideoGAIA: A Benchmark for General AI Assistants on Agentic Video Understanding
Fan Zhang, Guangming Yao, Jinyang Wu +6
Video understanding is a fundamental task for evaluating the capabilities of multimodal large language models (MLLMs). However, existing leading models have already achieved approx…
ATOM: Geometry-Aware Microgesture towards Object-Agnostic Tangible Interaction
Yinqiao Wang, Hao Xu, Qixuan Liu +3
This paper presents ATOM, an integrated framework towards agnostic and tangible object interactions with microgestures. Our goal is to support microgesture interactions across diff…
VideoCoCo: Code-as-CoT for Physically-Consistent Video Generation via an Agentic Dual-Engine System
Haodong Li, Tianfei Ren, Xiaoxiao Ma +25
Text-to-video models have achieved remarkable visual quality, yet they still struggle to generate physically consistent dynamics because the temporal evolution of a scene must be i…
Support Operation Factorization: Compositional Readout of Frozen Vision Encoders under Controlled Interventions
Zhongyao Wang, Wanli Ouyang, Taoyong Cui +1
Compositional analysis of frozen vision encoders should determine both what changed and where it changed. Standard factor probes score these axes separately, however, and can rewar…
LiverPlan: A Stage-Adaptive Immersive Visual Analytics Framework for Anatomical Liver Surgical Planning
Qixuan Liu, Shi Qiu, Xiwen Wu +7
Anatomical liver resection (ALR) surgery is the most important treatment for liver cancer, yet preoperative planning demands complex, multi-stage clinical reasoning under competing…
ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness
Qiao Yan, Yihan Wang, Zhenghao Xing +2
Autonomous driving under adverse weather remains a critical challenge, yet existing vision-language benchmarks mainly evaluate under standard conditions, synthetic corruptions, or…
Native Active Perception as Reasoning for Omni-Modal Understanding
Zhenghao Xing, Ruiyang Xu, Yuxuan Wang +8
Passive models for long video understanding typically rely on a "watch-it-all" paradigm, processing frames uniformly regardless of query difficulty, causing computational cost to g…
Be Your Own Teacher: Steering Protein Language Models via Unsupervised Reward Optimization
Lanqing Li, Shentong Mo, Yang Yu +1
Protein language models (PLMs) have emerged as powerful tools for controllable biomolecular design, yet their post-training adaptation typically relies on costly wet-lab validation…
Orchestra-o1: Omnimodal Agent Orchestration
Fan Zhang, Vireo Zhang, Shengju Qian +8
The recent success of agent swarms has shifted the paradigm of large language model (LLM)-based agents from single-agent workflows to multi-agent systems, highlighting the importan…
EPS3D: End-to-End Feed-Forward 3D Panoptic Segmentation
Runsong Zhu, Jiaxin Guo, Xiaoyang Guo +9
This paper introduces EPS3D, a new end-to-end feed-forward framework for open-vocabulary 3D panoptic segmentation. Unlike existing methods relying on additional preprocessing, we d…
Fast Image Super-Resolution via Consistency Rectified Flow
Jiaqi Xu, Wenbo Li, Haoze Sun +8
Diffusion models (DMs) have demonstrated remarkable success in real-world image super-resolution (SR), yet their reliance on time-consuming multi-step sampling largely hinders thei…
ATLAS: Agentic or Latent Visual Reasoning? One Word is Enough for Both
Ziyu Guo, Rain Liu, Xinyan Chen +1
Visual reasoning, often interleaved with intermediate visual states, has emerged as a promising direction in the field. A straightforward approach is to directly generate images vi…
Does Engram Do Memory Retrieval in Autoregressive Image Generation?
Jinghao Wang, Qiyuan He, Chunbin Gu +1
The Engram module -- a hash-keyed, O(1) associative memory injected into Transformer layers -- was recently shown to improve large language model pretraining, with the appealing in…
LaST-R1: Reinforcing Robotic Manipulation via Adaptive Physical Latent Reasoning
Hao Chen, Jiaming Liu, Zhonghao Yan +10
Robotic foundation models require reasoning over complex visual scenes to execute adaptive actions in dynamic environments. While recent studies on latent-reasoning Vision-Language…
OmniShow: Unifying Multimodal Conditions for Human-Object Interaction Video Generation
Donghao Zhou, Guisheng Liu, Hao Yang +9
In this work, we study Human-Object Interaction Video Generation (HOIVG), which aims to synthesize high-quality human-object interaction videos conditioned on text, reference image…
MME-CoF-Pro: Evaluating Reasoning Coherence in Video Generative Models with Text and Visual Hints
Yu Qi, Xinyi Xu, Ziyu Guo +10
Video generative models show emerging reasoning behaviors. It is essential to ensure that generated events remain causally consistent across frames for reliable deployment, a prope…
Look Before Acting: Enhancing Vision Foundation Representations for Vision-Language-Action Models
Yulin Luo, Hao Chen, Zhuangzhe Wu +10
Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for robotic manipulation, in which reliable action prediction critically depends on accurately int…