National University of Singapore

Headlines · 2

1. 16h
   QuantWM targets flicker in 2-bit video-world-model caches

   Researchers from iLearn-Lab at Harbin Institute of Technology (Shenzhen) and LV-Lab at the National University of Singapore propose QuantWM, a training-free framework for 2-bit KV Cache quantization in video world models. The team says its query-sensitive clustering and low-rank attention compensation improve visual stability while achieving up to 6.20x KV Cache compression across five evaluated models.

   机器之心 · 🔥 6
2. 2d
   Apple's RISED uses rubrics for multi-environment agent training

   Apple Machine Learning Research published RISED, a method that repurposes rubrics to guide online data selection and policy supervision when training a single LLM agent jointly across diverse interactive environments. An LLM judge tags each rollout with a rubric vocabulary shared across environments; the resulting profiles select data that matches the mixed-environment batch's behavioural composition while limiting overlap, positive rubrics provide privileged context for an on-policy self-distillation teacher's token-level supervision, and negative rubrics steer later rollouts away from recurring failure modes. The paper reports that across model backbones RISED achieves the highest mean pass rate across environments and ranks first or second in every individual environment.

   Apple Machine Learning Research · 🔥 3

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