activity
20182026
most citedBilateral Reference for High-Resolution Dichotomous Image Segmentation

74 citations · 469 across the 219 of their papers we have counts for

collaborators

248 papers

cs.CL2026

Beyond Retrieval Failure: Understanding Why LLMs Miss Evidence in Multi-Hop RAG

Jiaqi Wei, Wenxuan Huang, Chengdong Xu +2

Multi-hop retrieval-augmented generation (RAG) requires an agent to retrieve evidence for a sequence of dependent sub-questions. When a wrong answer lacks a required passage, the p…

cs.CE2026

PROTEAN: Beyond De Novo Generation - Can LLM Agents Perform Text-Guided Protein Structure Editing?

Encheng Su, Xinping Liu, Yizhou Wang +11

Generative AI has achieved remarkable success in de novo protein design, yet protein engineering typically begins with existing, characterized proteins. The primary demand is targe…

cs.LG2026

GRAM: Correcting Frozen Time-Series Foundation Models via Graph-Retrieved Amplitude Memory

Xiaoyun Yu, Xiangfei Qiu, Yonggui Huang +7

Time-series foundation models (TSFMs) enable zero-shot forecasting through large-scale cross-domain pretraining, while retrieval augmentation further improves their performance by…

cs.RO2026

RoboBridge: A Self-Evolving Embodied Agent Framework for Sim-to-Real Transfer

Chenxi Li, Zhangrui Zhao, Rui Li +8

A key challenge in bringing embodied intelligence into the real world is transferring capabilities from simulation to reality and enabling agents to continually adapt after deploym…

cs.CE2026

SymbolicLM: Training Language Models as Symbolic Regressors

Jun Yao, Yingfan Hua, Ruikun Li +4

Large Language Models (LLMs) have shown promising capabilities in scientific reasoning, yet scientific discovery ultimately requires deriving precise laws directly from observation…

cs.CL2026

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…

cs.LG2026

An immune world model for multiscale forecasting and therapeutic hypothesis generation

Taoyong Cui, Xi Wang, Zonghang Li +11

Immune therapies act across cell-intrinsic programs, tissue ecosystems, and patient-specific immune states, yet most predictors address these scales separately. We used a governed…

cond-mat.mtrl-sci2026

Diagnosing and narrowing the simulation-to-real gap in powder X-ray diffraction with a wet-dry agentic loop

Shaoguang Wang, Weiyu Guo, Ben Fei +3

Powder X-ray diffraction (PXRD) is the routine probe of crystalline matter, yet its analysis is the rate-limiting step as laboratories automate acquisition. Deep-learning analyzers…

cs.CL2026

When LLM Meets Tree Search: A Systematic View of Inference as Search in Large Language Models

Jiaqi Wei, Xiang Zhang, Yuejin Yang +10

As pretraining scaling laws approach saturation, Test-Time Scaling (TTS) has emerged as an important direction for improving reasoning by allocating inference-time compute to a fix…

cs.LG2026

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…

cs.CV2026

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…

cs.CV2026

Video-DeepResearch: Towards the Next-Generation Multimodal Deepresearch Agent

Zhen Fang, Yu Zeng, Wenxuan Huang +17

We introduce Video-DeepResearch (Video-DR), extending multimodal agents from static images to continuous video streams, a setting that demands dense spatiotemporal grounding couple…

cs.MA2026

SeekBrain: An Autonomous Multi-Agent System for Accelerating Neuroscience Discovery

Jiamin Wu, Peishan Xiang, Jingyang Chen +26

Modern neuroscience relies on integrating multi-scale, multimodal datasets to uncover the neural principles underlying intelligence. However, analytical challenges posed by highly…

cs.RO2026

LabRobFail: A Benchmark for Robotic Failure Analysis in Chemical Self-driving Laboratory

Haobo Wang, Baoli Sun, Anqi Zou +8

The deployment of embodied agents in self-driving laboratories could accelerate scientific discovery, yet their reliability is constrained by the irreversible and safety-critical n…

cs.CL2026

Accurate, Interdisciplinary and Transparent Structure-property Understanding with Deep Native Structural Reasoning

Chen Tang, Yizhou Wang, Jianyu Wu +26

Structure-property relationships are foundational to biology, chemistry and materials science, where function, reactivity and physical response emerge from spatial, chemical and pe…

cs.CV2026

PVCap: Towards Accurate 3D Dense Captioning via PseudoCap and VoxelCapNet

Xiaopei Wu, Chenshu Hou, Liang Peng +9

3D dense captioning, an emerging vision-language task, aims to generate descriptive sentences for each object in the 3D scene. Despite the impressive results achieved by previous m…

cs.LG2026

ResearchClawBench: A Benchmark for End-to-End Autonomous Scientific Research

Wanghan Xu, Shuo Li, Tianlin Ye +48

AI coding agents are increasingly used for scientific work, but their end-to-end autonomous research capability remains difficult to verify. We present ResearchClawBench, a benchma…

cs.CV2026

BrainJanus: A Unified Model for Understanding and Generation across Brain, Vision, and Language

Haitao Wu, Qirui Zhang, Zhouheng Yao +8

Modeling the bidirectional correspondence between external sensory stimuli and internal neural activity has emerged as a critical frontier in neuroscience. However, existing approa…

cs.CV2026

Heterogeneous and Adept Snapshot Distillation for 3D Semantic Segmentation

Xiaopei Wu, Yuenan Hou, Junkai Xu +7

Multi-modal fusion and multi-model ensembling are prevalent in enhancing the performance of 3D semantic segmentation. Despite the impressive performance, these methods either rely…

cs.AI2026

LabOSBench: Benchmarking Computer Use Agents for Scientific Instrument Control

Anqi Zou, Han Deng, Chengyu Zhang +9

Current computer-use benchmarks primarily focus on software operation tasks in virtualized systems, whereas scientific instrumentation scenarios require coordinated control over co…

cs.CL2026

SciOrch: Learning to Orchestrate Expert LLMs for Solving Frontier Multimodal Scientific Reasoning Tasks

Jingru Guo, Xiangyuan Xue, Lian Zhang +6

Frontier scientific reasoning remains a major challenge for large language models (LLMs), where even the strongest commercial systems fall short of expert-level performance. A clos…

cs.RO2026

Trans2Occ: Voxel Occupancy Estimation and Grasp for Transparent Objects from Simulation to Reality

Yixuan Yang, Sha Zhang, Rui Li +12

Transparent objects remain challenging for robotic perception due to unreliable depth sensing caused by refraction and reflection. While prior approaches rely on multi-view reconst…

cs.AI2026

OmniMatBench: A Human-Calibrated Multimodal Reasoning Benchmark Across 19 Materials Science Subfields

Wanhao Liu, Jiaqing Xie, Qian Tan +10

As multimodal language models play an increasingly important role in scientific research, materials science offers a critical testbed due to its interdisciplinary, multimodal, and…

cs.CV2026

LabBuilder: Protocol-Grounded 3D Layout Generation for Interactable and Safe Laboratory

Jianbao Cao, Zhangrui Zhao, Bohan Feng +15

Automated laboratories hold the promise of accelerating scientific discovery, yet their deployment is bottlenecked by the difficulty of designing safe and executable environments.…