2 papers
cs.SD2026
What Matters in Preference Post-Training of Continuous Autoregressive Speech Language Models
Yingda Shen, Yao Qian, Dekun Chen +6
Continuous autoregressive speech language models combine an autoregressive (AR) backbone with a diffusion or flow-matching head. Preference post-training requires choosing how to c…
cs.LG2026
Understanding the Weight Averaging Mechanism in LLM Training for Post-Training Quantization
Hanzhang Wang, Tianqi Shen, Zonglin Liu +3
Large language models (LLMs) are typically pretrained in high precision but increasingly deployed with low-precision post-training quantization (PTQ). Recent studies have shown tha…