closed-loop inference 1model calibration 1post-training quantization 1robotic manipulation 1world action models 1
From the 1 of 2 linked papers with an AI index.
2 papers
cs.CL2026
AWARe: Mitigating Catastrophic Forgetting via Activation-Weighted Adaptive REtention
Juncheng Liao, Jinfan Lv, Guoming Wang +3
Multimodal Large Language Models (MLLMs) exhibit strong generalization and reasoning abilities due to large-scale multimodal pre-training. However, fine-tuning these models on down…
cs.AI2026
QuantWAMs: Calibrating at the Right Granularity for World Action Models
Jiacheng Zhou, Jinfan Lv, Ruixuan Li +4
The paper proposes QuantWAMs, a post‑training quantization framework that tailors quantization decisions to the structure, rollout distribution, and task objectives of World Action…