22 papers
Visual Representation Matters: Exploiting Temporal Differences in Video-to-Audio Generation
Zehua Chen, Junyou Wang, Yuxuan Jiang +5
Video-to-audio (V2A) generation extends image-to-audio generation (I2A) by introducing consecutive frames that provide essential temporal cues for audio synthesis. However, existin…
KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels
Han Wang, Jintao Zhang, Kai Jiang +3
LLM-based Triton kernel generation has attracted significant interest, yet a fundamental empirical question remains unanswered: where does this capability break down, and why? We p…
Deterministic Differentiable Structured Pruning for Large Language Models
Weiyu Huang, Pengle Zhang, Xiaolu Zhang +3
Structured pruning reduces LLM inference cost by removing low-importance architectural components. This can be viewed as learning a multiplicative gate for each component under an…
TetraJet-v2: Accurate NVFP4 Training for Large Language Models with Oscillation Suppression and Outlier Control
Yuxiang Chen, Yifan Liu, Xiaoming Xu +5
Large Language Models (LLMs) training is prohibitively expensive, driving interest in low-precision fully-quantized training (FQT). While novel 4-bit formats like NVFP4 offer subst…
SageBwd: A Trainable Low-bit Attention
Jintao Zhang, Marco Chen, Haoxu Wang +5
Low-bit attention, such as SageAttention, has emerged as an effective approach for accelerating model inference, but its applicability to training remains poorly understood. In pri…
SLA: Beyond Sparsity in Diffusion Transformers via Fine-Tunable Sparse-Linear Attention
Jintao Zhang, Haoxu Wang, Kai Jiang +10
In Diffusion Transformer (DiT) models, particularly for video generation, attention latency is a major bottleneck due to the long sequence length and the quadratic complexity. We f…