215 citations · 216 across the 17 of their papers we have counts for
19 papers
SpecCoder: Specification-Aware Code Generation with Curriculum Dual-Task Reinforcement Learning
Yixuan Li, Mingxuan Huang, Jiajing Wang +4
Large language models (LLMs) have made substantial progress in code generation but still struggle with challenging programming tasks that require understanding rich natural languag…
Obshazard-bench: Benchmarking Multimodal Foundation Models for Real-Time Disaster Intelligence from Raw Earth Observation Streams
Fengxiang Wang, Qiuyang Yu, Yueying Li +14
Multimodal Large Language Models (MLLMs) are increasingly used to interpret Earth observation data, yet their capability to support real-world disaster emergency response remains i…
From Coarse to Fine: Managing Temporal Granularity in Spatio-Temporal Data for Fine-Grained Traffic Prediction
Shuhao Li, Weidong Yang, Yue Cui +4
Efficient acquisition, storage, and utilization of traffic data are critical challenges in spatio-temporal data management. Most traffic data systems collect and store observations…
GenericAgent: A Token-Efficient Self-Evolving LLM Agent via Contextual Information Density Maximization (V1.0)
Jiaqing Liang, Jinyi Han, Weijia Li +15
Long-horizon large language model (LLM) agents are fundamentally limited by context. As interactions become longer, tool descriptions, retrieved memories, and raw environmental fee…
MedThink: Enhancing Diagnostic Accuracy in Small Models via Teacher-Guided Reasoning Correction
Xinchun Su, Chunxu Luo, Lipeng Ma +2
Accurate clinical diagnosis requires extensive domain knowledge and complex clinical reasoning capabilities. Although large language models (LLMs) hold great potential for clinical…
Lifecycle-Aware code generation: Leveraging Software Engineering Phases in LLMs
Xing Xing, Wei Wang, Lipeng Ma +2
Recent progress in large language models (LLMs) has advanced automatic code generation, yet most approaches rely on direct, single-step translation from problem descriptions to cod…
MedCritical: Enhancing Medical Reasoning in Small Language Models via Self-Collaborative Correction
Xinchun Su, Chunxu Luo, Yixuan Li +2
In the field of medicine, complex reasoning tasks such as clinical diagnosis, treatment planning, and medical knowledge integration pose significant challenges, where small languag…
LogReasoner: Empowering LLMs with Expert-like Coarse-to-Fine Reasoning for Automated Log Analysis
Lipeng Ma, Yixuan Li, Weidong Yang +7
Log analysis is crucial for monitoring system health and diagnosing failures in complex systems. Recent advances in large language models (LLMs) offer new opportunities for automat…
PseudoBridge: Pseudo Code as the Bridge for Better Semantic and Logic Alignment in Code Retrieval
Yixuan Li, Xinyi Liu, Weidong Yang +4
Code retrieval aims to find relevant code snippets matching natural language queries within massive codebases, playing a vital role in software development. Recent advances leverag…
DeepThink3D: Enhancing Large Language Models with Programmatic Reasoning in Complex 3D Situated Reasoning Tasks
Jiayi Song, Rui Wan, Lipeng Ma +4
This work enhances the ability of large language models (LLMs) to perform complex reasoning in 3D scenes. Recent work has addressed the 3D situated reasoning task by invoking tool…
Fine-Grained Traffic Inference from Road to Lane via Spatio-Temporal Graph Node Generation
Shuhao Li, Weidong Yang, Yue Cui +4
Fine-grained traffic management and prediction are fundamental to key applications such as autonomous driving, lane change guidance, and traffic signal control. However, obtaining…
Multi-modal Multi-task Pre-training for Improved Point Cloud Understanding
Liwen Liu, Weidong Yang, Lipeng Ma +1
Recent advances in multi-modal pre-training methods have shown promising effectiveness in learning 3D representations by aligning multi-modal features between 3D shapes and their c…
ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation
Xinyi Liu, Lipeng Ma, Yixuan Li +5
Large Language Models (LLMs) are widely used across various scenarios due to their exceptional reasoning capabilities and natural language understanding. While LLMs demonstrate str…
AdaptiveLog: An Adaptive Log Analysis Framework with the Collaboration of Large and Small Language Model
Lipeng Ma, Weidong Yang, Yixuan Li +6
Automated log analysis is crucial to ensure high availability and reliability of complex systems. The advent of LLMs in NLP has ushered in a new era of language model-driven automa…
IceDiff: High Resolution and High-Quality Sea Ice Forecasting with Generative Diffusion Prior
Jingyi Xu, Siwei Tu, Weidong Yang +6
Variation of Arctic sea ice has significant impacts on polar ecosystems, transporting routes, coastal communities, and global climate. Tracing the change of sea ice at a finer scal…
LUK: Empowering Log Understanding with Expert Knowledge from Large Language Models
Lipeng Ma, Weidong Yang, Sihang Jiang +6
Logs play a critical role in providing essential information for system monitoring and troubleshooting. Recently, with the success of pre-trained language models (PLMs) and large l…
Lightening Anything in Medical Images
Ben Fei, Yixuan Li, Weidong Yang +5
The development of medical imaging techniques has made a significant contribution to clinical decision-making. However, the existence of suboptimal imaging quality, as indicated by…
Towards Unified Representation of Multi-Modal Pre-training for 3D Understanding via Differentiable Rendering
Ben Fei, Yixuan Li, Weidong Yang +2
State-of-the-art 3D models, which excel in recognition tasks, typically depend on large-scale datasets and well-defined category sets. Recent advances in multi-modal pre-training h…
Comprehensive Review of Deep Learning-Based 3D Point Cloud Completion Processing and Analysis
Ben Fei, Weidong Yang, Wenming Chen +5
Point cloud completion is a generation and estimation issue derived from the partial point clouds, which plays a vital role in the applications in 3D computer vision. The progress…