1 citations · 1 across the 12 of their papers we have counts for
14 papers
Mr.LHDR: A Benchmark for Multimodal Real-World Long-Horizon Deep Research Agents
Minghao Guo, Meng Cao, Sui Zhao +10
Deep research agents are increasingly capable of web search, tool use, multimodal evidence analysis, and information synthesis. However, existing benchmarks mainly evaluate medium-…
SAB-LVLM: Significance-Aware Binarization for Large Vision-Language Models
Qi Lyu, Jiahua Dong, Baichen Liu +7
Large Vision-Language Models (LVLMs) have achieved remarkable progress in multimodal understanding, yet their enormous parameter scale and cross-modal computation incur substantial…
LatentPilot: Scene-Aware Vision-and-Language Navigation by Dreaming Ahead with Latent Visual Reasoning
Haihong Hao, Lei Chen, Mingfei Han +5
Existing vision-and-language navigation (VLN) models primarily reason over past and current visual observations, while largely ignoring the future visual dynamics induced by action…
Beyond Dense Futures: World Models as Structured Planners for Robotic Manipulation
Minghao Jin, Mozheng Liao, Mingfei Han +2
Recent world-model-based Vision-Language-Action (VLA) architectures have improved robotic manipulation through predictive visual foresight. However, dense future prediction introdu…
GeoSense: Internalizing Geometric Necessity Perception for Multimodal Reasoning
Ruiheng Liu, Haihong Hao, Mingfei Han +4
Advancing towards artificial superintelligence requires rich and intelligent perceptual capabilities. A critical frontier in this pursuit is overcoming the limited spatial understa…
Implicit Geometry Representations for Vision-and-Language Navigation from Web Videos
Mingfei Han, Haihong Hao, Liang Ma +6
Vision-and-Language Navigation (VLN) has long been constrained by the limited diversity and scalability of simulator-curated datasets, which fail to capture the complexity of real-…
See, Plan, Rewind: Progress-Aware Vision-Language-Action Models for Robust Robotic Manipulation
Tingjun Dai, Mingfei Han, Tingwen Du +6
Measurement of task progress through explicit, actionable milestones is critical for robust robotic manipulation. This progress awareness enables a model to ground its current task…
CARE What Fails: Contrastive Anchored-REflection for Verifiable Multimodal Reasoning
Yongxin Wang, Zhicheng Yang, Meng Cao +5
Group-relative reinforcement learning with verifiable rewards (RLVR) often wastes the most informative data it already has the failures. When all rollouts are wrong, gradients stal…
BLAZER: Bootstrapping LLM-based Manipulation Agents with Zero-Shot Data Generation
Rocktim Jyoti Das, Harsh Singh, Diana Turmakhan +5
Scaling data and models has played a pivotal role in the remarkable progress of computer vision and language. Inspired by these domains, recent efforts in robotics have similarly f…
PhyBlock: A Progressive Benchmark for Physical Understanding and Planning via 3D Block Assembly
Liang Ma, Jiajun Wen, Min Lin +12
While vision-language models (VLMs) have demonstrated promising capabilities in reasoning and planning for embodied agents, their ability to comprehend physical phenomena, particul…
EvolveNav: Empowering LLM-Based Vision-Language Navigation via Self-Improving Embodied Reasoning
Bingqian Lin, Yunshuang Nie, Khun Loun Zai +10
Recent studies have revealed the potential of training open-source Large Language Models (LLMs) to unleash LLMs' reasoning ability for enhancing vision-language navigation (VLN) pe…
EACO: Enhancing Alignment in Multimodal LLMs via Critical Observation
Yongxin Wang, Meng Cao, Haokun Lin +5
Multimodal large language models (MLLMs) have achieved remarkable progress on various visual question answering and reasoning tasks leveraging instruction fine-tuning specific data…
RoomTour3D: Geometry-Aware Video-Instruction Tuning for Embodied Navigation
Mingfei Han, Liang Ma, Kamila Zhumakhanova +5
Vision-and-Language Navigation (VLN) suffers from the limited diversity and scale of training data, primarily constrained by the manual curation of existing simulators. To address…
MALMM: Multi-Agent Large Language Models for Zero-Shot Robotics Manipulation
Harsh Singh, Rocktim Jyoti Das, Mingfei Han +2
Large Language Models (LLMs) have demonstrated remarkable planning abilities across various domains, including robotics manipulation and navigation. While recent efforts in robotic…