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20232026
most citedDoes DetectGPT Fully Utilize Perturbation? Bridging Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Better

1 citations · 2 across the 12 of their papers we have counts for

collaborators

13 papers

cs.LG2026

Episodic Memory Temporal Consistency for Cooperative Multi-Agent Reinforcement Learning

Zicheng Zhao, Yu Lan, Chengzhengxu Li +2

Cooperative Multi-Agent Reinforcement Learning (MARL) frequently suffers from severe reward sparsity and exploration bottlenecks. While episodic memory mechanisms mitigate these is…

cs.AI2026

Thinking as Compression: Your Reasoning Model is Secretly a Context Compressor

Guoxin Ma, Yibing Liu, Chengzhengxu Li +7

Context compression aims to shorten long context inputs with minimal information loss for LLM inference acceleration. While existing methods have shown promise, they typically rely…

cs.CR2026

MGTEVAL: An Interactive Platform for Systemtic Evaluation of Machine-Generated Text Detectors

Yuanfan Li, Qi Zhou, Chengzhengxu Li +5

We present MGTEVAL, an extensible platform for systematic evaluation of Machine-Generated Text (MGT) detectors. Despite rapid progress in MGT detection, existing evaluations are of…

cs.CL2026

Confidence Should Be Calibrated More Than One Turn Deep

Zhaohan Zhang, Chengzhengxu Li, Xiaoming Liu +3

Large Language Models (LLMs) are increasingly applied in high-stakes domains such as finance, healthcare, and education, where reliable multi-turn interactions with users are essen…

cs.CV2026

MLLM-4D: Towards Visual-based Spatial-Temporal Intelligence

Xingyilang Yin, Chengzhengxu Li, Jiahao Chang +2

Humans are born with vision-based 4D spatial-temporal intelligence, which enables us to perceive and reason about the evolution of 3D space over time from purely visual inputs. Des…

cs.CL2025

DEER: Disentangled Mixture of Experts with Instance-Adaptive Routing for Generalizable Machine-Generated Text Detection

Guoxin Ma, Xiaoming Liu, Hongyang Chen +6

Detecting machine-generated text has become a critical challenge amid the rapid advancement of LLMs, yet existing detectors degrade severely under domain shift. Through systematic…