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Nemotron-Labs-Diffusion: A Tri-Mode Language Model Unifying Autoregressive, Diffusion, and Self-Speculation Decoding
Yonggan Fu, Lexington Whalen, Abhinav Garg +23
We introduce Nemotron-Labs-Diffusion, a tri-mode language model (LM) that unifies AR, diffusion, and self-speculation decoding within a single architecture. Trained with a joint AR…
Now You Hear Me: Audio Narrative Attacks Against Large Audio-Language Models
Ye Yu, Haibo Jin, Yaoning Yu +2
Large audio-language models increasingly operate on raw speech inputs, enabling more seamless integration across domains such as voice assistants, education, and clinical triage. T…
PREMISE: Scalable and Strategic Prompt Optimization for Efficient Mathematical Reasoning in Large Models
Ye Yu, Yaoning Yu, Haohan Wang
Large reasoning models (LRMs) such as Claude 3.7 Sonnet and OpenAI o1 achieve strong performance on mathematical benchmarks using lengthy chain-of-thought (CoT) reasoning, but the…
SIPDO: Closed-Loop Prompt Optimization via Synthetic Data Feedback
Yaoning Yu, Ye Yu, Peiyan Zhang +3
Prompt quality plays a critical role in the performance of large language models (LLMs), motivating a growing body of work on prompt optimization. Most existing methods optimize pr…