3 articles tagged with #parametric-models. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.
Researchers introduce ToolSense, a diagnostic framework that reveals significant gaps in how large language models understand tools despite strong retrieval performance. Testing on ~47k tools shows parametric models collapse by 50-64% on realistic queries compared to benchmark performance, suggesting current evaluation methods mask fundamental knowledge deficiencies.
Researchers introduce IDEA, a framework that converts Large Language Model decision-making into interpretable, editable parametric models with calibrated probabilities. The approach outperforms major LLMs like GPT-5.2 and DeepSeek R1 on benchmarks while enabling direct expert knowledge integration and precise human-AI collaboration.
Researchers introduce SAM 3D Animal, a promptable framework for reconstructing multiple animals in 3D from single images, addressing key challenges like occlusion and species variation. The team also releases Herd3D, a new multi-animal dataset with over 5K images, achieving state-of-the-art results across multiple benchmarks.
