7 papers
MOVA: Towards Scalable and Synchronized Video-Audio Generation
OpenMOSS Team, Donghua Yu, Mingshu Chen +38
Audio is indispensable for real-world video, yet generation models have largely overlooked audio components. Current approaches to producing audio-visual content often rely on casc…
SimpleTool: Parallel Decoding for Real-Time LLM Function Calling
Xiaoxin Shi, Jiaxin Wan, Linkang Dong +3
LLM-based function calling enables intelligent agents to interact with external tools and environments, yet autoregressive decoding imposes a fundamental latency bottleneck that li…
DiRL: An Efficient Post-Training Framework for Diffusion Language Models
Ying Zhu, Jiaxin Wan, Xiaoran Liu +7
Diffusion Language Models (dLLMs) have emerged as promising alternatives to Auto-Regressive (AR) models. While recent efforts have validated their pre-training potential and accele…
Beyond Real: Imaginary Extension of Rotary Position Embeddings for Long-Context LLMs
Xiaoran Liu, Yuerong Song, Zhigeng Liu +6
Rotary Position Embeddings (RoPE) have become a standard for encoding sequence order in Large Language Models (LLMs) by applying rotations to query and key vectors in the complex p…
Sparse-dLLM: Accelerating Diffusion LLMs with Dynamic Cache Eviction
Yuerong Song, Xiaoran Liu, Ruixiao Li +5
Diffusion Large Language Models (dLLMs) enable breakthroughs in reasoning and parallel decoding but suffer from prohibitive quadratic computational complexity and memory overhead d…
Beyond Homogeneous Attention: Memory-Efficient LLMs via Fourier-Approximated KV Cache
Xiaoran Liu, Siyang He, Qiqi Wang +9
Large Language Models struggle with memory demands from the growing Key-Value (KV) cache as context lengths increase. Existing compression methods homogenize head dimensions or rel…