most citedOmniSapiens: A Foundation Model for Social Behavior Processing via Heterogeneity-Aware Relative Policy Optimization

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

collaborators

10 papers

cs.AI20262 cited

OmniSapiens: A Foundation Model for Social Behavior Processing via Heterogeneity-Aware Relative Policy Optimization

Keane Ong, Sabri Boughorbel, Luwei Xiao +9

Socially intelligent AI systems must reason across diverse human behavioral tasks and generalize to new social contexts. However, behavioral data is inherently heterogeneous, compr…

cs.LG2026

SPRI: SVD-Partitioned Residual Initialization for Data-Constrained MoE Upcycling

Weiqiao Shan, Ruixiang Mao, Yuang Li +10

Mixture-of-Experts (MoE) models enable efficient scaling, but training them from scratch remains prohibitively expensive. MoE upcycling mitigates this cost by converting pretrained…

cs.CV2026

AudioFace: Language-Assisted Speech-Driven Facial Animation with Multimodal Language Models

Kai Zheng, Zejian Kang, Rui Mao +4

Speech-driven facial animation requires accurate correspondence between acoustic signals and facial motion, especially for articulation-related mouth movements. However, directly m…

cs.CL2026

Affective Flow Language Model for Emotional Support Conversation

Chenghui Zou, Ning Wang, Tiesunlong Shen +5

Large language models (LLMs) have been widely applied to emotional support conversation (ESC). However, complex multi-turn support remains challenging.This is because existing alig…

cs.CL2026

LexGenius: An Expert-Level Benchmark for Large Language Models in Legal General Intelligence

Wenjin Liu, Haoran Luo, Xin Feng +6

Legal general intelligence (GI) refers to artificial intelligence (AI) that encompasses legal understanding, reasoning, and decision-making, simulating the expertise of legal exper…

cs.CL2026

Prompt-R1: Collaborative Automatic Prompting Framework via End-to-end Reinforcement Learning

Wenjin Liu, Haoran Luo, Xueyuan Lin +5

Recently, advanced large language models (LLMs) have emerged at an increasingly rapid pace. However, when faced with complex problems, most users are often unable to provide accura…