Qwen3-1.7B

Intel researchers introduced BITCOS, a weight storage format that leverages the high sparsity of ternary models to achieve 1.485 bits per weight. This innovation improves inference throughput on Intel CPUs and GPUs by reducing the amount of data moved through memory.

The paper introduces TTPO, a method designed to optimize LLM reasoning during test-time training by utilizing asymmetric learning signals from pseudo-labels. It effectively mitigates the risks of noisy majority-vote labels by distilling agreeing rollouts and penalizing disagreeing ones.

The paper introduces TTPO, a method designed to optimize LLM reasoning during test-time training by utilizing asymmetric learning signals from pseudo-labels. It effectively mitigates the risks of noisy majority-vote labels by distilling agreeing rollouts and penalizing disagreeing ones.

This research expands on Anthropic's 'Verbalizable-Workspace' paper by applying J-space measurements to open-source models. It characterizes the internal structure of LLMs as having distinct functional zones and demonstrates that steering influence decays via a power law.