collaborators

9 papers

cs.CL2026

Hidden Decoding at Scale: Latent Computation Scaling for Large Language Models

Aiwei Liu, Cheng Shi, Chuhan Wu +44

Scaling Large Language Models (LLMs) has been driven mainly by enlarging the Transformer backbone, but for an already-strong model this requires another round of costly pretraining…

cs.LG2026

RLCSD: Reinforcement Learning with Contrastive On-Policy Self-Distillation

Leyi Pan, Shuchang Tao, Yunpeng Zhai +5

On-policy self-distillation (OPSD) provides dense, token-level supervision for reasoning models by aligning a model's own distribution with the distribution it produces under privi…

cs.CL2026

UniAudio-Token: Empowering Semantic Speech Tokenizers with General Audio Perception

Yuhan Song, Linhao Zhang, Aiwei Liu +6

Semantic speech tokenizers have become a widely used interface for Audio-LLMs, owing to their compact single-codebook design and strong linguistic alignment. However, their focus o…

cs.PF2026

How Much Parallelism Is "Free"? A Principle of Near-Free Parallelism for Parallel Decoding

Minghua He, Lingzhe Zhang, Yuan Liu +2

Parallel decoding improves generation efficiency by processing multiple decode positions within a single decode forward, but reported speedups conflate algorithmic token utilizatio…

cs.CV2026

DiffSpot: Can VLMs Spot Fine-Grained Visual Differences in Web Interfaces?

Linhao Zhang, Aiwei Liu, Yuan Liu +1

Vision-language models (VLMs) have made strong progress on high-level image-text alignment, yet their ability to perceive subtle visual differences remains limited. We study this p…

cs.CL2026

Beyond Transcription: Unified Audio Schema for Perception-Aware AudioLLMs

Linhao Zhang, Yuhan Song, Aiwei Liu +6

Recent Audio Large Language Models (AudioLLMs) exhibit a striking performance inversion: while excelling at complex reasoning tasks, they consistently underperform on fine-grained…