5 citations · 12 across the 32 of their papers we have counts for
21 papers · 1 filter
Modality Alignment across Trees on Heterogeneous Hyperbolic Manifolds
Wei Wu, Xiaomeng Fan, Yuwei Wu +4
Modality alignment is critical for vision-language models (VLMs) to effectively integrate information across modalities. However, existing methods extract hierarchical features fro…
Demystifying the Roles of LLM Layers in Retrieval, Knowledge, and Reasoning
Xinyuan Song, Keyu Wang, PengXiang Li +2
Recent studies suggest that the deeper layers of Large Language Models (LLMs) contribute little to representation learning and can often be removed without significant performance…
Efficient Multi-turn RL for GUI Agents via Decoupled Training and Adaptive Data Curation
Pengxiang Li, Zechen Hu, Zirui Shang +15
Vision-language model (VLM) based GUI agents show promise for automating complex desktop and mobile tasks, but face significant challenges in applying reinforcement learning (RL):…
Discrete Diffusion for Reflective Vision-Language-Action Models in Autonomous Driving
Pengxiang Li, Yinan Zheng, Yue Wang +6
End-to-End (E2E) solutions have emerged as a mainstream approach for autonomous driving systems, with Vision-Language-Action (VLA) models representing a new paradigm that leverages…
Diffusion Language Models Know the Answer Before Decoding
Pengxiang Li, Yefan Zhou, Dilxat Muhtar +5
Diffusion language models (DLMs) have recently emerged as an alternative to autoregressive approaches, offering parallel sequence generation and flexible token orders. However, the…
InfiGUI-G1: Advancing GUI Grounding with Adaptive Exploration Policy Optimization
Yuhang Liu, Zeyu Liu, Shuanghe Zhu +10
The emergence of Multimodal Large Language Models (MLLMs) has propelled the development of autonomous agents that operate on Graphical User Interfaces (GUIs) using pure visual inpu…
GPAS: Accelerating Convergence of LLM Pretraining via Gradient-Preserving Activation Scaling
Tianhao Chen, Xin Xu, Zijing Liu +12
Modern Large Language Models, such as the LLaMA, Qwen and DeepSeek series, predominantly adopt the Pre-LayerNorm (Pre-LN) Transformer architecture. While being stable during pretra…
DriveAgent-R1: Advancing VLM-based Autonomous Driving with Active Perception and Hybrid Thinking
Weicheng Zheng, Xiaofei Mao, Nanfei Ye +4
The advent of Vision-Language Models (VLMs) has significantly advanced end-to-end autonomous driving, demonstrating powerful reasoning abilities for high-level behavior planning ta…
Geometry-aware Distance Measure for Diverse Hierarchical Structures in Hyperbolic Spaces
Pengxiang Li, Yuwei Wu, Zhi Gao +5
Learning in hyperbolic spaces has attracted increasing attention due to its superior ability to model hierarchical structures of data. Most existing hyperbolic learning methods use…
A Set-to-Set Distance Measure in Hyperbolic Space
Pengxiang Li, Wei Wu, Zhi Gao +6
We propose a hyperbolic set-to-set distance measure for computing dissimilarity between sets in hyperbolic space. While point-to-point distances in hyperbolic space effectively cap…
Double-Checker: Enhancing Reasoning of Slow-Thinking LLMs via Self-Critical Fine-Tuning
Xin Xu, Tianhao Chen, Fan Zhang +11
While slow-thinking large language models (LLMs) exhibit reflection-like reasoning, commonly referred to as the "aha moment:, their ability to generate informative critiques and re…
From Objects to Anywhere: A Holistic Benchmark for Multi-level Visual Grounding in 3D Scenes
Tianxu Wang, Zhuofan Zhang, Ziyu Zhu +5
3D visual grounding has made notable progress in localizing objects within complex 3D scenes. However, grounding referring expressions beyond objects in 3D scenes remains unexplore…
Adaptive Classifier-Free Guidance via Dynamic Low-Confidence Masking
Pengxiang Li, Shilin Yan, Joey Tsai +4
Classifier-Free Guidance (CFG) significantly enhances controllability in generative models by interpolating conditional and unconditional predictions. However, standard CFG often e…
Adaptive Chain-of-Focus Reasoning via Dynamic Visual Search and Zooming for Efficient VLMs
Xintong Zhang, Zhi Gao, Bofei Zhang +8
Vision language models (VLMs) have achieved impressive performance across a variety of computer vision tasks. However, the multimodal reasoning capability has not been fully explor…
TransDiffuser: Diverse Trajectory Generation with Decorrelated Multi-modal Representation for End-to-end Autonomous Driving
Xuefeng Jiang, Yuan Ma, Pengxiang Li +7
In recent years, diffusion models have demonstrated remarkable potential across diverse domains, from vision generation to language modeling. Transferring its generative capabiliti…
InfiGUI-R1: Advancing Multimodal GUI Agents from Reactive Actors to Deliberative Reasoners
Yuhang Liu, Pengxiang Li, Congkai Xie +5
Multimodal Large Language Models (MLLMs) have powered Graphical User Interface (GUI) Agents, showing promise in automating tasks on computing devices. Recent works have begun explo…
Iterative Tool Usage Exploration for Multimodal Agents via Step-wise Preference Tuning
Pengxiang Li, Zhi Gao, Bofei Zhang +8
Multimodal agents, which integrate a controller e.g., a vision language model) with external tools, have demonstrated remarkable capabilities in tackling complex multimodal tasks.…
Learning Personalized Driving Styles via Reinforcement Learning from Human Feedback
Derun Li, Changye Li, Yue Wang +9
Generating human-like and adaptive trajectories is essential for autonomous driving in dynamic environments. While generative models have shown promise in synthesizing feasible tra…
InfiR : Crafting Effective Small Language Models and Multimodal Small Language Models in Reasoning
Congkai Xie, Shuo Cai, Wenjun Wang +17
Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) have made significant advancements in reasoning capabilities. However, they still face challenges such as…
The Curse of Depth in Large Language Models
Wenfang Sun, Xinyuan Song, Pengxiang Li +3
In this paper, we introduce the Curse of Depth, a concept that highlights, explains, and addresses the recent observation in modern Large Language Models (LLMs) where nearly half o…
InfiGUIAgent: A Multimodal Generalist GUI Agent with Native Reasoning and Reflection
Yuhang Liu, Pengxiang Li, Zishu Wei +7
Graphical User Interface (GUI) Agents, powered by multimodal large language models (MLLMs), have shown great potential for task automation on computing devices such as computers an…