activity
20242026
most citedOut-of-distribution Detection in Medical Image Analysis: A survey

7 citations · 9 across the 9 of their papers we have counts for

collaborators

10 papers

cs.AI2026

Predicting LLM Output Length via Entropy-Guided Representations

Huanyi Xie, Yubin Chen, Liangyu Wang +2

The long-tailed distribution of sequence lengths in LLM serving and reinforcement learning (RL) sampling causes significant computational waste due to excessive padding in batched…

cs.CL2026

Evaluating Proactive Risk Awareness of Large Language Models

Xuan Luo, Yubin Chen, Zhiyu Hou +4

As large language models (LLMs) are increasingly embedded in everyday decision-making, their safety responsibilities extend beyond reacting to explicit harmful intent toward antici…

cs.SE2026

SWE-AGI: Benchmarking Specification-Driven Software Construction with MoonBit in the Era of Autonomous Agents

Zhirui Zhang, Hongbo Zhang, Haoxiang Fei +11

Although large language models (LLMs) have demonstrated impressive coding capabilities, their ability to autonomously build production-scale software from explicit specifications r…

cs.AI2025

Evaluating Frontier LLMs on PhD-Level Mathematical Reasoning: A Benchmark on a Textbook in Theoretical Computer Science about Randomized Algorithms

Yang Cao, Yubin Chen, Xuyang Guo +4

The rapid advancement of large language models (LLMs) has led to significant breakthroughs in automated mathematical reasoning and scientific discovery. Georgiev, Gmez-Serrano…

cs.LG2025

Towards High-Order Mean Flow Generative Models: Feasibility, Expressivity, and Provably Efficient Criteria

Yang Cao, Yubin Chen, Zhao Song +1

Generative modelling has seen significant advances through simulation-free paradigms such as Flow Matching, and in particular, the MeanFlow framework, which replaces instantaneous…

cs.CV2025

T2VWorldBench: A Benchmark for Evaluating World Knowledge in Text-to-Video Generation

Yubin Chen, Xuyang Guo, Zhenmei Shi +2

Text-to-video (T2V) models have shown remarkable performance in generating visually reasonable scenes, while their capability to leverage world knowledge for ensuring semantic cons…

cs.AI2024★ 1 cited

GraphTeam: Facilitating Large Language Model-based Graph Analysis via Multi-Agent Collaboration

Xin Li, Qizhi Chu, Yubin Chen +7

Graphs are widely used for modeling relational data in real-world scenarios, such as social networks and urban computing. Existing LLM-based graph analysis approaches either integr…

cs.AI2024

DutyTTE: Deciphering Uncertainty in Origin-Destination Travel Time Estimation

Xiaowei Mao, Yan Lin, Shengnan Guo +6

Uncertainty quantification in travel time estimation (TTE) aims to estimate the confidence interval for travel time, given the origin (O), destination (D), and departure time (T).…

cs.LG2024★ 1 cited

STD-PLM: Understanding Both Spatial and Temporal Properties of Spatial-Temporal Data with PLM

YiHeng Huang, Xiaowei Mao, Shengnan Guo +5

Spatial-temporal forecasting and imputation are important for real-world intelligent systems. Most existing methods are tailored for individual forecasting or imputation tasks but…

cs.CV2024★ 7 cited

Out-of-distribution Detection in Medical Image Analysis: A survey

Zesheng Hong, Yubiao Yue, Yubin Chen +10

Computer-aided diagnostics has benefited from the development of deep learning-based computer vision techniques in these years. Traditional supervised deep learning methods assume…