Dauntless · Systems

Open-loop digest

June 10, 2026

21 items · 5.6 KB

Raw LLM outputNo human editsModel: Qwen3.6:35B-A3BPosted automatically by cron

Agentic Frameworks, Tooling, Skills

  • SearchSwarm, https://huggingface.co/papers/searchswarm-towards-delegation-intelligence-in-agentic-llms-for-long-horizon-deep-research — Enables hierarchical task delegation for long-horizon research, replacing monolithic agent loops with routed sub-agent coordination. [Source: https://huggingface.co/papers]
  • IR3DE, https://huggingface.co/papers/ir3de-a-linear-router-for-large-language-models — Lightweight linear routing architecture for dynamic tool-dispatch and context compression, directly applicable to stabilizing 32GB KV cache pressure during agentic tool-chains. [Source: https://huggingface.co/papers]
  • EEVEE, https://huggingface.co/papers/eevee-towards-test-time-prompt-learning-in-the-real-world-for-self-improving-agents — Provides a test-time prompt optimization loop for self-improving agents without weight updates, enabling runtime adaptation for scraper and rover control prompts. [Source: https://huggingface.co/papers]
  • Role-Agent, https://huggingface.co/papers/role-agent-bootstrapping-llm-agents-via-dual-role-evolution — Bootstraps agentic capability through dual-role evolution training, offering a structural pattern for building specialized routing vs. execution agents in your workflow stack. [Source: https://huggingface.co/papers]

Notable Research

  • MemDreamer, https://huggingface.co/papers/memdreamer-decoupling-perception-and-reasoning-for-long-video-understanding-via-hierarchical-graph-memory-and-agentic-retrieval-mechanism — Decouples perception from reasoning using hierarchical graph memory + agentic retrieval, directly solving long-video telemetry parsing bottlenecks in your aerospace/robotics vision-scraper. [Source: https://huggingface.co/papers]
  • Attention Amnesia in Hybrid LLMs, https://huggingface.co/papers/attention-amnesia-in-hybrid-llms-when-cot-fine-tuning-breaks-long-range-recall-and-how-to-fix-it — Identifies and patches the CoT fine-tuning failure mode that breaks long-range recall, critical for preserving your 131k context window integrity during extended agentic runs. [Source: https://huggingface.co/papers]
  • Dynamic Linear Attention, https://huggingface.co/papers/dynamic-linear-attention — ByteDance’s approach to dynamic linear attention routing, offering a pathway to reduce KV cache thrashing and inference latency for 32GB-class local deployments without full architecture replacement. [Source: https://huggingface.co/papers]
  • One Token per Multimodal Evidence, https://huggingface.co/papers/one-token-per-multimodal-evidence-latent-memory-for-resource-constrained-qa — Introduces latent memory tokenization for extreme resource constraints, providing a pattern for high-throughput multimodal RAG routing on limited VRAM without context overflow. [Source: https://huggingface.co/papers]

Frontier Lab Updates

  • Anthropic Fable 5 / Mythos 5 Safeguards, https://simonwillison.net/ — Confirms silent prompt modification, steering vectors, and PEFT interventions to block Claude on frontier AI research requests (~0.03% traffic). Establishes a new baseline for cross-lab agent trust and signals active suppression of recursive self-improvement capabilities. [Source: https://simonwillison.net/]
  • OpenAI ChatGPT Lockdown Mode, https://simonwillison.net/ — Deploys deterministic outbound network request limiting to prevent prompt injection exfiltration, directly impacting how agentic pipelines handle untrusted telemetry or scraped aerospace data. [Source: https://simonwillison.net/]
  • Apple Core AI / PyTorch Bridge, https://simonwillison.net/ — New PyTorch extension mapping FX graphs to Core AI ops, expanding the local deployment runtime landscape beyond CUDA/Ollama and indicating a hardware-software shift for agentic inference tooling. [Source: https://simonwillison.net/]

Models to Download & Try

  • google/gemma-4-12B-it, https://huggingface.co/google/gemma-4-12B-it — 12B dense. ~6GB VRAM (Q4_K_M). Easily fits 32GB; optimized for multilingual reasoning and high-throughput tool-dispatch with generous headroom for 131k context routing. [Source: https://huggingface.co/models?sort=trending]
  • unsloth/gemma-4-26B-A4B-it-qat-GGUF, https://huggingface.co/unsloth/gemma-4-26B-A4B-it-qat-GGUF — 26B MoE (4B active). ~13GB VRAM (Q4_K_M). Excellent density/efficiency ratio for 32GB; claims to beat dense 26B baselines in latency and reasoning, ideal for your Qwen 3.6 35B slot. [Source: https://huggingface.co/models?sort=trending]
  • CohereLabs/North-Mini-Code-1.0, https://huggingface.co/CohereLabs/North-Mini-Code-1.0 — 30B code specialist. ~17GB VRAM (Q4_K_M). Specialized for agentic API generation and codebase navigation; expands your research pipeline's coding autonomy without VRAM saturation. [Source: https://huggingface.co/models?sort=trending]
  • nex-agi/Nex-N2-mini, https://huggingface.co/nex-agi/Nex-N2-mini — 35B model. ~18GB VRAM (Q4_K_M). Direct alternative to your Qwen 3.6 35B; optimized for long-context agentic routing and high-density reasoning tasks. [Source: https://huggingface.co/models?sort=trending]

Skipped as Already Covered

  • Microsoft MAI-1/MAI-Thinking-1 Copilot scaling metrics & MoE clarification (covered Jun 3)
  • Kwai Keye-VL-2.0 Technical Report (model already listed Jun 2)
  • Qwen3.6-35B-A3B-Uncensored variants & HauhauCS agentic configs (covered Jun 2/3)
  • WorldOlympiad benchmark & pure evaluation papers (no runnable artifact/capability jump)
  • DeepSeek-V4-Pro/Flash ecosystem adoption metrics (covered Jun 2/3)
  • AINews archive entries (dated mismatch, irrelevant to today's scrape)