deepswe-729fdc7c·4 events·first seen Aliases: DeepSWE
MindForge is an automated pipeline that converts open-source command-line programs into source-free training environments exposing only compiled executables and documentation, enabling training data generation for from-scratch program synthesis. Using GLM-5.2 as a teacher agent, the authors fine-tune Qwen3.6-27B on synthesized trajectories, raising its ProgramBench pass rate from 37.98% to 49.51% and achieving gains across seven held-out benchmarks including SWE-bench Verified (+5.04) and RepoZero-C2Rust (+31.00). The work addresses a gap in coding agent training infrastructure by spanning the full software engineering life cycle rather than single-phase tasks. The result is notable for achieving frontier-comparable performance on a 27B model through targeted data curation.
Meta Superintelligence Labs has released Muse Spark 1.1, a significant upgrade to Muse Spark featuring a 1-million-token context window, strong agentic and computer-use capabilities, and major coding improvements on complex codebases. The model supports multi-agent orchestration, zero-shot generalization to MCP servers and custom tools, and multimodal reasoning including visual-to-code generation and video understanding. Alongside the model release, Meta is launching a public preview of the Meta Model API, giving developers programmatic access for the first time. Safety evaluations were conducted under Meta's Advanced AI Scaling Framework across frontier risk categories.
Three new benchmarks — DeepSWE (by Datacurve), ProgramBench (Meta/Stanford/Harvard), and ITBench-AA (IBM/Artificial Analysis) — are positioned as more rigorous replacements for the SWE-bench family, which models have largely saturated. DeepSWE tests feature implementation using private codebases and human-written problems; ProgramBench evaluates agents' ability to recreate functional programs from scratch; ITBench-AA measures root-cause diagnosis in real-world IT incident scenarios. Current top performers include GPT-5.5 (70% on DeepSWE), Claude Opus 4.7 (46.7% on ITBench-AA), and Claude Opus 4.7 (3% on ProgramBench at the 95% pass threshold), illustrating that even frontier models have substantial headroom.
This edition of The Batch covers five distinct AI developments: Datacurve's DeepSWE benchmark claims to fix critical grading flaws in SWE-bench Pro with hand-written verifiers and harder tasks; DeepSeek permanently cuts V4 Pro prices by 75%; Microsoft's MAI-Image-2.5 debuts third on the Arena leaderboard; Anthropic's Claude Mythos Preview found over 10,000 high/critical vulnerabilities in the first month of Project Glasswing, with remediation badly lagging discovery; and the Model Context Protocol proposes removing stateful sessions to enable stateless, load-balanced remote servers. Each item reflects meaningful movement in evaluation methodology, inference economics, multimodal generation, AI-assisted security, and agent tooling infrastructure.