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Person: "akshay_pachaar"
not much happened today
glm-4.6v glm-4.6v-flash jina-vlm-2b hugging-face zhipu-ai jina-ai google-deepmind axiomprover fine-tuning multimodality model-optimization long-context mechanistic-interpretability formal-methods sequence-architectures reinforcement-learning lioronai akshay_pachaar _akhaliq ben_burtenshaw vllm_project prince_canuma zenmuxai eliebakouch theturingpost axiommathai neelnanda5 sarahookr
Claude Code Skills gains attention with a published talk and Hugging Face's new "skill" enabling one-line fine-tuning pipelines for models from ~0.5B to 70B parameters, supporting SFT, DPO, and GRPO, costing as low as ~$0.30 for small runs. Zhipu AI launches multimodal models GLM-4.6V (106B params MoE) and GLM-4.6V-Flash (9B dense), featuring 128k context and native multimodal function calling, with free Flash variant and API pricing detailed. Jina AI releases Jina-VLM (2B), a compact multilingual VLM excelling in diagrams and documents with top benchmark scores. At NeurIPS 2025, research highlights include Google's post-Transformer sequence architectures (Moneta, Yaad, Memora) showing up to 20% gains in long-context retrieval, AxiomProver's autonomous Lean system solving 9/12 Putnam 2025 problems rapidly, and mechanistic interpretability advances discussed by Chris Olah emphasizing scalable tooling.