3 papers
cs.CL2025
WeDLM: Reconciling Diffusion Language Models with Standard Causal Attention for Fast Inference
Aiwei Liu, Minghua He, Shaoxun Zeng +7
Autoregressive (AR) generation is the standard decoding paradigm for Large Language Models (LLMs), but its token-by-token nature limits parallelism at inference time. Diffusion Lan…
cs.CV2025
POINTS-Reader: Distillation-Free Adaptation of Vision-Language Models for Document Conversion
Yuan Liu, Zhongyin Zhao, Le Tian +8
High-quality labeled data is essential for training accurate document conversion models, particularly in domains with complex formats such as tables, formulas, and multi-column tex…
cs.CL2025
WildSpeech-Bench: Benchmarking End-to-End SpeechLLMs in the Wild
Linhao Zhang, Jian Zhang, Bokai Lei +4
Recent multi-modal Large Language Models (LLMs) such as GPT-4o have demonstrated strong capabilities of direct speech interaction. However, the lack of specialized and comprehensiv…