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Daily notes on new models, LLM releases, agent frameworks and AI research, written from the sources we follow and delivered as a newsletter every day.
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Research1 min read
XAI-Arena, a new framework, uses LLMs to evaluate the quality of XAI explanations, offering a scalable and reproducible method for comparison. Human ratings correlate strongly with LLM assessments, providing a systematic approach to evaluating XAI methods.
From arXiv cs.AI
LLMs1 min read
CARRE is a three-stage framework combining action retrieval, counterfactual scoring, and LLM reasoning for churn prescription. It achieves significant risk reduction compared to baseline methods and demonstrates improved explanation quality through prompt refinement.
How this blog is made
Each feed entry becomes one request to OpenSmartRoute: the router picks a model with a cost-weighted objective, the editorial-writer skill is layered on the prompt, and the outcome trains the learners - the same pipeline available to every workspace.
Open any post to see which target answered, its confidence, the alternatives and what the request cost. Run the same pipeline yourself: register feeds in the operator console, map a small model under Providers, or call POST /api/v1/route with execute: true.
From arXiv cs.CL
Research1 min read
EnvCraft is a framework for creating synthetic, executable environments to accelerate Agentic RL training for claw-like agents. Experiments with Qwen3/3.5 models show significant performance gains and reduced inference costs.
From arXiv cs.AI
Research1 min read
Research demonstrates that LLM tool agents can be improved by modifying their runtime harnesses – prompts and middleware – without retraining the underlying model. This protocol, using PRISM, achieves significant performance gains on benchmarks like BFCL, tau2-Retail, and tau2-Telecom, prioritizing reliability alongside lift.
From arXiv cs.AI
Research1 min read
A six-month study of two LLM trading agent fleets reveals significant operational factors impacting performance. The research highlights the importance of the operating layer, volatility-blind sizing, and the lack of directional edges in these autonomous agents.
From arXiv cs.AI
LLMs1 min read
AuditForecast is a new agentic scaffold that improves forecasting accuracy and auditability by structuring the forecasting process with explicit evidence aggregation and probability updates. It outperforms existing agentic baselines and expensive deep-research agents while maintaining a favorable cost-accuracy tradeoff.
From arXiv cs.CL
Research1 min read
Microsoft Research released Skala 1.1, an updated deep-learning exchange-correlation functional for predictive DFT. This update expands accessibility and provides a benchmark for tracking computational performance.
From Microsoft Research
LLMs1 min read
This report details the evolving state of open models, focusing on size trends, licensing options, and key performance indicators for models deployed in production environments. It highlights shifts in model architecture and accessibility for engineers.
From Hugging Face blog
Posts are drafted from public feeds by models OpenSmartRoute routes to - the same router, skill and metering customers use - and always link to the original source. Corrections: support.
