activity
20232026
most citedSelfEvolve: A Code Evolution Framework via Large Language Models

18 citations · 23 across the 14 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

Agentic Active Omni-Modal Perception for Multi-Hop Audio-Visual Reasoning

Ke Xu, Yuhao Wang, Ziyang Cheng +3

Multi-hop audio-visual reasoning remains challenging for Omni-LLMs, as relevant evidence is often sparse, temporally dispersed, and distributed across both audio and visual streams…

cs.AI2026

From Reactive to Proactive: Assessing the Proactivity of Voice Agents via ProVoice-Bench

Ke Xu, Yuhao Wang, Yu Wang

Recent advancements in LLM agents are gradually shifting from reactive, text-based paradigms toward proactive, multimodal interaction. However, existing benchmarks primarily focus…

cs.CL2026

Cross-Modal Coreference Alignment: Enabling Reliable Information Transfer in Omni-LLMs

Hongcheng Liu, Yuhao Wang, Zhe Chen +5

Omni Large Language Models (Omni-LLMs) have demonstrated impressive capabilities in holistic multi-modal perception, yet they consistently falter in complex scenarios requiring syn…

cs.CL2026

VocalNet-MDM: Accelerating Streaming Speech LLM via Self-Distilled Masked Diffusion Modeling

Ziyang Cheng, Yuhao Wang, Heyang Liu +4

Recent Speech Large Language Models~(LLMs) have achieved impressive capabilities in end-to-end speech interaction. However, the prevailing autoregressive paradigm imposes strict se…

cs.AI2026

Miner:Mining Intrinsic Mastery for Data-Efficient RL in Large Reasoning Models

Shuyang Jiang, Yuhao Wang, Ya Zhang +2

Current critic-free RL methods for large reasoning models suffer from severe inefficiency when training on positive homogeneous prompts (where all rollouts are correct), resulting…