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

7 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

SHALA-LLM: Smartly Handling Ambiguous Labels in Aligning LLMs

Jingyao Wu, Ashley Wang, Keane Ong +2

Many human-centered tasks, including natural language inference (NLI) and emotion recognition (ER), have multiple plausible interpretations, leading to label ambiguity and challeng…

cs.AI2026

Human Behavior Atlas: Benchmarking Unified Psychological and Social Behavior Understanding

Keane Ong, Wei Dai, Carol Li +8

Using intelligent systems to perceive psychological and social behaviors, that is, the underlying affective, cognitive, and pathological states that are manifested through observab…

cs.CL2026

<SOG_k>: One LLM Token for Explicit Graph Structural Understanding

Jingyao Wu, Bin Lu, Zijun Di +5

Large language models show great potential in unstructured data understanding, but still face significant challenges with graphs due to their structural hallucination. Existing app…

eess.AS2026

AmbER: Dual Ambiguity-Aware Emotion Recognition Applied to Speech and Text

Jingyao Wu, Grace Lin, Yinuo Song +1

Emotion recognition is inherently ambiguous, with uncertainty arising both from rater disagreement and from discrepancies across modalities such as speech and text. There is growin…

cs.AI2025

When One Modality Sabotages the Others: A Diagnostic Lens on Multimodal Reasoning

Chenyu Zhang, Minsol Kim, Shohreh Ghorbani +4

Despite rapid growth in multimodal large language models (MLLMs), their reasoning traces remain opaque: it is often unclear which modality drives a prediction, how conflicts are re…