4 papers · 1 filter
AttSVD:Prompt-Adaptive Low-Rank KV Cache Compression via Attention-Guided SVD
Sara Abdali, Jongwoo Ko, Pashmina Cameron
The key-value (KV) cache of autoregressive transformers grows linearly with context length and dominates memory at long context. Most training-free remedies evict low-importance to…
Eliciting Weak-to-Strong Generalization with On-Policy Reverse Distillation
Youngrok Park, Sangmin Bae, Hojung Jung +6
Weak-to-strong generalization asks whether stronger models can learn from weaker supervisors and surpass them. This is particularly important for successive model generations and m…
Scaling Reasoning Efficiently via Relaxed On-Policy Distillation
Jongwoo Ko, Sara Abdali, Young Jin Kim +2
On-policy distillation (OPD) is a promising approach for transferring reasoning capabilities to capacity-constrained models, yet sampled-token OPD often suffers from entropy collap…
StableQAT: Stable Quantization-Aware Training at Ultra-Low Bitwidths
Tianyi Chen, Sihan Chen, Xiaoyi Qu +5
Quantization-aware training (QAT) is essential for deploying large models under strict memory and latency constraints, yet achieving stable and robust optimization at ultra-low bit…