Find a story
Search Spins
Search titles, summaries, and missing voices across published articles — press releases, announcements, and media coverage.
5 results for “tool use”
AgentPatch: Coarse-to-Fine Weak-Task Repair for Merging Agentic Multimodal Large Language Models
Researchers introduced AgentPatch, a training-free method to repair performance degradation in merged agentic multimodal large language models (MLLMs), specifically addressing weak-task failure and behavior-critical forgetting after model merging.
Aug 10, 2026
Benchmarks Are Not Validation: A System-Level View of Financial LLM Applications
The article argues that benchmark scores alone are insufficient for validating large language models in financial applications, advocating instead for system-level validation across data, model design, retrieval, generation, agent behavior, governance, and implementation.
Aug 3, 2026
New Databricks tool uses AI agents to rewrite legacy SQL at scale - infoworld.com
Databricks announced a new AI-powered tool that automates the rewriting of legacy SQL code at enterprise scale, positioning it as a solution to technical debt and cloud migration bottlenecks.
Published Jul 30, 2026 · Analyzed Aug 3, 2026
Opus 5 improves coding, reasoning efficiency, and prompt-cache-friendly tool use, and is priced at $5/1M input tokens and $25/1M output, same as Opus 4.8 (David Gewirtz/ZDNET)
Anthropic released Opus 5, a new large language model version claiming improved coding and reasoning efficiency plus better prompt-caching support for tool use, at unchanged pricing versus Opus 4.8.
Jul 24, 2026
Controlling Tool Use with Heading-Specific Activation Steering
Researchers propose a method to steer tool-augmented LLMs toward more selective tool invocation using heading-anchored steering vectors, demonstrating causal suppression across five open-source models—but find the underlying geometry is irregular and inconsistent with linear encoding assumptions.
Jul 9, 2026