collaborators

14 papers

cs.AI2026

Mini-BEHAVIOR-Gran: Revealing U-Shaped Effects of Instruction Granularity on Language-Guided Embodied Agents

Sukai Huang, Chenyuan Zhang, Fucai Ke +4

Instruction granularity is an important yet poorly controlled variable in language-guided embodied AI. Existing benchmarks typically pair each task with a single static instruction…

cs.CL2026

MCBench: A Multicontext Safety Assessment Benchmark for Omni Large Language Models

Manh Luong, Tamas Abraham, Junae Kim +6

Existing multimodal safety benchmarks focus solely on visual inputs and cannot assess Omni Large Language Models (LLMs) that process vision, audio, and text. We introduce MCBench,…

cs.SD2026

Resurfacing Paralinguistic Awareness in Large Audio Language Models

Hao Yang, Minghan Wang, Tongtong Wu +3

Large Audio Language Models (LALMs) have expanded the interaction with human to speech modality, which introduces great interactive potential, due to the paralinguistic cues implic…

cs.AI2026

LiveCultureBench: a Multi-Agent, Multi-Cultural Benchmark for Large Language Models in Dynamic Social Simulations

Viet-Thanh Pham, Lizhen Qu, Thuy-Trang Vu +2

Large language models (LLMs) are increasingly deployed as autonomous agents, yet evaluations focus primarily on task success rather than cultural appropriateness or evaluator relia…

eess.AS2026

Unbiased Sliced Wasserstein Kernels for High-Quality Audio Captioning

Manh Luong, Khai Nguyen, Dinh Phung +2

Audio captioning systems face a fundamental challenge: teacher-forcing training creates exposure bias that leads to caption degeneration during inference. While contrastive methods…

cs.CL2025

IRIS: An Iterative and Integrated Framework for Verifiable Causal Discovery in the Absence of Tabular Data

Tao Feng, Lizhen Qu, Niket Tandon +1

Causal discovery is fundamental to scientific research, yet traditional statistical algorithms face significant challenges, including expensive data collection, redundant computati…