activity
20212026
most citedRiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization

4 citations · 6 across the 9 of their papers we have counts for

collaborators

9 papers

cs.SD2026

Audio-Anchored Fusion of Multi-Ratio DiT Reconstruction Residuals for Cross-Domain Audio Deepfake Detection

Haotian Mo, Jie Liu, Siqi Shen +8

Audio deepfake detectors often degrade when generators, corpora, or recording conditions change. We use a Diffusion Transformer (DiT), trained only on bona fide speech, as a frozen…

cs.LG2026

MAGE: Multi-scale Autoregressive Generation for Offline Reinforcement Learning

Chenxing Lin, Xinhui Gao, Haipeng Zhang +7

Generative models have gained significant traction in offline reinforcement learning (RL) due to their ability to model complex trajectory distributions. However, existing generati…

cs.CV2025

Measuring the Unspoken: A Disentanglement Model and Benchmark for Psychological Analysis in the Wild

Yigui Feng, Qinglin Wang, Haotian Mo +7

Generative psychological analysis of in-the-wild conversations faces two fundamental challenges: (1) existing Vision-Language Models (VLMs) fail to resolve Articulatory-Affective A…

cs.AI2025

PlanU: Large Language Model Reasoning through Planning under Uncertainty

Ziwei Deng, Mian Deng, Chenjing Liang +7

Large Language Models (LLMs) are increasingly being explored across a range of reasoning tasks. However, LLMs sometimes struggle with reasoning tasks under uncertainty that are rel…

cs.CL2024

Dovetail: A CPU/GPU Heterogeneous Speculative Decoding for LLM inference

Libo Zhang, Zhaoning Zhang, Baizhou Xu +4

With the continuous advancement in the performance of large language models (LLMs), their demand for computational resources and memory has significantly increased, which poses maj…

cs.MA2023★ 4 cited

RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization

Siqi Shen, Chennan Ma, Chao Li +5

Multi-agent systems are characterized by environmental uncertainty, varying policies of agents, and partial observability, which result in significant risks. In the context of Mult…