1 citations · 2 across the 16 of their papers we have counts for
19 papers
Action Shaping: Policies Absorb What They Can Express
Yanjun Chen, Jinghan Wang, Xiaoyu Shen +2
Reward shaping has a theorem: a potential-based term can be removed without changing the optimal policy. The same practice on the action channel, an offset added in training and dr…
Natural-Language Policies to Executable Decisions: An Interpretable Large Language Model Framework
Ziqiang Zhang, Jing Ma, Zilong Wang +6
Pricing automation in large-scale tourism is challenging because travel orders are highly unstructured, while pricing policies are complex, rapidly evolving, and inherently open-en…
FlashNav: Training Deployable Robot Navigation Policies in Seconds
Shanze Wang, Yiwei Qian, Xinming Zhang +8
Training Deep Reinforcement Learning (DRL) navigation policies for different robot configurations remains time-consuming. We present FlashNav, a GPU-based framework that trains rob…
Evaluation Before Generation: A Paradigm for Robust Multimodal Sentiment Analysis with Missing Modalities
Rongfei Chen, Tingting Zhang, Xiaoyu Shen +1
The missing modality problem poses a fundamental challenge in multimodal sentiment analysis, significantly degrading model accuracy and generalization in real world scenarios. Exis…
MMEB-V3: Measuring the Performance Gaps of Omni-Modality Embedding Models
Haohang Huang, Xuan Lu, Mingyi Su +9
Multimodal embedding models aim to map heterogeneous inputs, such as text, images, videos, and audio, into a shared semantic space. However, existing methods and benchmarks remain…
CeRLP: A Cross-embodiment Robot Local Planning Framework for Visual Navigation
Haoyu Xi, Mingao Tan, Xinming Zhang +5
Visual navigation for cross-embodiment robots is challenging due to variations in robot and camera configurations, which can lead to the failure of navigation tasks. Previous appro…
SonicBench: Dissecting the Physical Perception Bottleneck in Large Audio Language Models
Yirong Sun, Yanjun Chen, Xin Qiu +8
Large Audio Language Models (LALMs) excel at semantic and paralinguistic tasks, yet their ability to perceive the fundamental physical attributes of audio such as pitch, loudness,…
PricingLogic: Evaluating LLMs Reasoning on Complex Tourism Pricing Tasks
Yunuo Liu, Dawei Zhu, Zena Al-Khalili +5
We present PricingLogic, the first benchmark that probes whether Large Language Models(LLMs) can reliably automate tourism-related prices when multiple, overlapping fare rules appl…
Informed Routing in LLMs: Smarter Token-Level Computation for Faster Inference
Chao Han, Yijuan Liang, Zihao Xuan +3
The deployment of large language models (LLMs) in real-world applications is increasingly limited by their high inference cost. While recent advances in dynamic token-level computa…
Context Guided Transformer Entropy Modeling for Video Compression
Junlong Tong, Wei Zhang, Yaohui Jin +1
Conditional entropy models effectively leverage spatio-temporal contexts to reduce video redundancy. However, incorporating temporal context often introduces additional model compl…
MA-ROESL: Motion-aware Rapid Reward Optimization for Efficient Robot Skill Learning from Single Videos
Xianghui Wang, Xinming Zhang, Yanjun Chen +2
Vision-language models (VLMs) have demonstrated excellent high-level planning capabilities, enabling locomotion skill learning from video demonstrations without the need for meticu…
Reasoning Beyond Language: A Comprehensive Survey on Latent Chain-of-Thought Reasoning
Xinghao Chen, Anhao Zhao, Heming Xia +7
Large Language Models (LLMs) have shown impressive performance on complex tasks through Chain-of-Thought (CoT) reasoning. However, conventional CoT relies on explicitly verbalized…
MAER-Nav: Bidirectional Motion Learning Through Mirror-Augmented Experience Replay for Robot Navigation
Shanze Wang, Mingao Tan, Zhibo Yang +4
Deep Reinforcement Learning (DRL) based navigation methods have demonstrated promising results for mobile robots, but suffer from limited action flexibility in confined spaces. Con…
Integrating Chain-of-Thought for Multimodal Alignment: A Study on 3D Vision-Language Learning
Yanjun Chen, Yirong Sun, Xinghao Chen +4
Chain-of-Thought (CoT) reasoning has proven effective in natural language tasks but remains underexplored in multimodal alignment. This study investigates its integration into 3D v…
Enhancing Deep Reinforcement Learning-based Robot Navigation Generalization through Scenario Augmentation
Shanze Wang, Mingao Tan, Zhibo Yang +4
This work focuses on enhancing the generalization performance of deep reinforcement learning-based robot navigation in unseen environments. We present a novel data augmentation app…
Beyond Visibility Limits: A DRL-Based Navigation Strategy for Unexpected Obstacles
Mingao Tan, Shanze Wang, Biao Huang +4
Distance-based reward mechanisms in deep reinforcement learning (DRL) navigation systems suffer from critical safety limitations in dynamic environments, frequently resulting in co…
Breaking the Pre-Planning Barrier: Adaptive Real-Time Coordination of Heterogeneous UAVs
Yuhan Hu, Yirong Sun, Yanjun Chen +3
Unmanned Aerial Vehicles (UAVs) offer significant potential in dynamic, perception-intensive tasks such as search and rescue and environmental monitoring; however, their effectiven…
Rethinking Soft Actor-Critic in High-Dimensional Action Spaces: The Cost of Ignoring Distribution Shift
Yanjun Chen, Xinming Zhang, Xianghui Wang +3
Soft Actor-Critic algorithm is widely recognized for its robust performance across a range of deep reinforcement learning tasks, where it leverages the tanh transformation to const…
Achieving Stable High-Speed Locomotion for Humanoid Robots with Deep Reinforcement Learning
Xinming Zhang, Xianghui Wang, Lerong Zhang +3
Humanoid robots offer significant versatility for performing a wide range of tasks, yet their basic ability to walk and run, especially at high velocities, remains a challenge. Thi…