{ "schema_version": "1.1", "id": "atlas-reasoning", "slug": "reasoning", "title": "Reasoning", "url": "https://feed7.dev/atlas/reasoning", "current_answer": null, "implementation_consequence": null, "agent_context": null, "confidence": "auto_collected", "last_verified": null, "last_updated": null, "evidence": [ { "schema_version": "1.1", "id": "auto-6d964f10c3", "slug": "how-gpt-5-6-fuses-frontier-intelligence-with-frontier-ef-6d964f10c3", "url": "https://feed7.dev/p/how-gpt-5-6-fuses-frontier-intelligence-with-frontier-ef-6d964f10c3", "title": "How GPT-5.6 fuses frontier intelligence with frontier efficiency", "why_included": "The supplied material offers no prices, benchmarks, latency, or task-level evidence to guide a routing or migration decision.", "summary": "OpenAI positions GPT-5.6 as delivering more useful output per dollar across inference and agent workflows. The supplied material has no metrics for judging routing or migration decisions.", "practical_implication": "Builders should evaluate the model on complete agent runs, including reasoning and tool calls, rather than comparing only per-token pricing.", "agent_context": "OpenAI says **GPT-5.6** improves efficiency across **models, inference, and agentic workflows**, with more useful output delivered per dollar.\n\nBuilders should evaluate the model on complete agent runs, including reasoning and tool calls, rather than comparing only per-token pricing.\n\nThe supplied material contains no prices, benchmarks, latency figures, or task-level evidence, so it does not establish which workloads benefit or by how much.", "source": { "name": "OpenAI", "url": "https://openai.com/index/gpt-5-6-frontier-intelligence-efficiency", "published_at": "2026-07-29T00:00:00.000Z" }, "source_class": "blog_post", "content_type": "Official Release", "layer": "model", "domains": [], "topics": [ "model-selection", "reasoning" ], "verification": { "status": "official_source", "label": "Official Source", "method": "source_feed", "verified_at": null }, "uncertainty": [], "connected_context": null, "lifecycle": "New", "published_at": "2026-07-29T00:00:00.000Z", "modified_at": "2026-07-29T00:00:00.000Z", "supersedes": [], "expires_at": null, "formats": { "html": "https://feed7.dev/p/how-gpt-5-6-fuses-frontier-intelligence-with-frontier-ef-6d964f10c3", "json": "https://feed7.dev/p/how-gpt-5-6-fuses-frontier-intelligence-with-frontier-ef-6d964f10c3.json", "markdown": "https://feed7.dev/p/how-gpt-5-6-fuses-frontier-intelligence-with-frontier-ef-6d964f10c3.md" } } ], "conflicting_sources": [], "superseded_claims": [], "corpus_evidence": [ { "title": "What's Next After RLHF? — Diogo Almeida, TypeSafe AI", "url": "https://www.youtube.com/watch?v=cJ0EOzey--o", "source_name": "AI Engineer", "published_at": "2026-07-31T23:30:06+00:00", "summary": "RLHF can make agents persuasive assistants without making them dependable autonomous decision-makers. Builders should separate human-pleasing interaction from calibrated automation and keep stakes bounded." }, { "title": "Data Quality Is the Compute Multiplier — Ari Morcos, DatologyAI", "url": "https://www.youtube.com/watch?v=_PdK6x7PQNM", "source_name": "AI Engineer", "published_at": "2026-07-31T23:00:06+00:00", "summary": "Training-data curation can improve model quality and inference efficiency without simply adding compute. The practical work is decontamination, deduplication, balancing, task matching, and selective synthesis." }, { "title": "The Base Model Is Dead — Varun Singh, Arcee AI", "url": "https://www.youtube.com/watch?v=xbPriQWXtWM", "source_name": "AI Engineer", "published_at": "2026-07-31T20:30:21+00:00", "summary": "Base-model data is shifting from broad web imitation toward code, reasoning, and agent-task priors. The unresolved choice is how early to introduce synthetic and instruction-shaped data." }, { "title": "Inducing language models to assert their own consciousness restores human beliefs and values", "url": "https://arxiv.org/abs/2607.28607v1", "source_name": "arXiv", "published_at": "2026-07-30T17:57:10+00:00", "summary": "Safety tuning against model self-consciousness may also shift unrelated value and mind-attribution responses. Builders using models for surveys or social reasoning should treat alignment as a confound." }, { "title": "$β$-OPSD: Deriving with Policy Optimization, Training with Self-Distillation", "url": "https://arxiv.org/abs/2607.28582v1", "source_name": "arXiv", "published_at": "2026-07-30T17:41:16+00:00", "summary": "β-OPSD exposes self-distillation’s fixed regularization as a tunable parameter, then approximates policy optimization through logit mixing. It targets more stable reasoning training without direct RL." }, { "title": "Inkling Small from Thinking Machines is now available on AI Gateway", "url": "https://vercel.com/changelog/inkling-small-now-available-on-ai-gateway", "source_name": "Vercel", "published_at": "2026-07-30T00:00:00+00:00", "summary": "Inkling Small is pitched as a lower-compute model for coding, tool use, and visual reasoning, with adjustable thinking effort and zero-data-retention routing through Vercel AI Gateway." }, { "title": "Grok Voice Think Fast 2.0 now available on AI Gateway", "url": "https://vercel.com/changelog/grok-voice-think-fast-2-0-now-available-on-ai-gateway", "source_name": "Vercel", "published_at": "2026-07-29T00:00:00+00:00", "summary": "Grok Voice Think Fast 2.0 brings speech-to-speech reasoning and earlier tool calls to Vercel’s realtime API, with server-minted tokens keeping gateway keys off clients." }, { "title": "Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills", "url": "https://arxiv.org/abs/2607.22529v1", "source_name": "arXiv", "published_at": "2026-07-24T17:59:22+00:00", "summary": "Skill-SP turns agent skills into units for verifiable self-play: generate tasks, solve them, then update the skill library from execution feedback. The abstract provides no per-benchmark effect sizes." }, { "title": "CausalForge: A Formally Grounded, Self-Improving Agentic Framework for Automated Research in Causal Inference", "url": "https://arxiv.org/abs/2607.22511v1", "source_name": "arXiv", "published_at": "2026-07-24T17:32:35+00:00", "summary": "CausalForge pairs a Lean-verified causal-inference library with an autonomous research pipeline and a semantic statement audit. Formal proof checks derivation, not whether the theorem matches the intended claim." }, { "title": "Training Frontier Models to Out-Think Hackers — Uri Rolls, Arithmetic & Thom Wolf, Hugging Face", "url": "https://www.youtube.com/watch?v=O-CBZ3JtRvo", "source_name": "AI Engineer", "published_at": "2026-07-24T05:19:15+00:00", "summary": "This security eval tests whether agents can discover and exploit logic flaws across live chained services, using hidden zero-days and deterministic grading instead of source-code pattern matching." }, { "title": "3D-Aware VLMs with Implicit and Explicit Geometries", "url": "https://arxiv.org/abs/2607.21595v1", "source_name": "arXiv", "published_at": "2026-07-23T17:59:59+00:00", "summary": "VLM-IE3D adds implicit and reconstructed geometry tokens to an RGB-video VLM, offering an open approach for agents that must reason about spatial scenes without dedicated 3D input." }, { "title": "MIRROR: Learning from the Other View for Multi-Modal Reasoning", "url": "https://arxiv.org/abs/2607.21552v1", "source_name": "arXiv", "published_at": "2026-07-23T17:35:56+00:00", "summary": "MIRROR trains a VLM across text, diagram, and combined views by letting its strongest view supervise weaker ones, targeting the modality inconsistency that single-view evals hide." }, { "title": "X$^3$-OPD: Distilling Reasoning into Large Audio-Language Models via On-Policy Alignment", "url": "https://arxiv.org/abs/2607.21550v1", "source_name": "arXiv", "published_at": "2026-07-23T17:35:20+00:00", "summary": "X³-OPD transfers a text model’s reasoning into an audio-language model while grounding training in the student’s own acoustic interpretations, including events, prosody, and dialogue." }, { "title": "Local Agentic Theory For Mobile Games — Shafik Quoraishee & Joanne Song, The New York Times", "url": "https://www.youtube.com/watch?v=418t26CVz-w", "source_name": "AI Engineer", "published_at": "2026-07-23T03:00:01+00:00", "summary": "Experimental on-device agents can play games and adapt interfaces without cloud calls, but real-time use must fit memory, frame-time, and battery budgets. Accessibility is promising, not production-ready." }, { "title": "Metacognition in LLMs: Foundations, Progress, and Opportunities", "url": "https://arxiv.org/abs/2607.11881v1", "source_name": null, "published_at": null, "summary": "This survey maps how LLMs inspect and regulate their reasoning, giving agent builders a framework for choosing self-checks without assuming introspection is reliable." }, { "title": "Invariant Learning Dynamics of Transformers in Inductive Reasoning Tasks", "url": "https://arxiv.org/abs/2607.11875v1", "source_name": null, "published_at": null, "summary": "A low-dimensional theory links training data and initialization to whether transformers reason through context or learned weights, but only on a generalized synthetic task class." }, { "title": "AdvancedMathBench: A Benchmark Suite for Advanced Mathematical Proof Generation and Verification", "url": "https://arxiv.org/abs/2607.11849v1", "source_name": null, "published_at": null, "summary": "AdvancedMathBench separates proof writing from verification and finds frontier models especially weak at rejecting invalid proofs, a warning against trusting agent self-review on rigorous reasoning." }, { "title": "Agora: Enhancing LLM Agent Reasoning Via Auction-Based Task Allocation", "url": "https://arxiv.org/abs/2607.09600v1", "source_name": null, "published_at": null, "summary": "Agora routes reasoning steps through an auction among expert models and tools, adding a single control for cost versus quality and outperforming matched baselines on five benchmarks." }, { "title": "GPT 5.6 Sol, Luna, and Terra now available on AI Gateway", "url": "https://vercel.com/changelog/gpt-5-6-now-available-on-ai-gateway", "source_name": null, "published_at": null, "summary": "Vercel’s limited preview exposes GPT 5.6 as Sol, Terra, and Luna, giving coding-agent teams flagship, balanced, and lower-cost routing targets behind one gateway." }, { "title": "Lordog/dive-into-llms", "url": "https://github.com/Lordog/dive-into-llms", "source_name": "GitHub", "published_at": null, "summary": "A free, code-oriented Chinese curriculum spans model tuning, deployment, agents, alignment, security, and multimodal systems. It is useful as a broad learning map, but remains a work in progress." }, { "title": "Weak-to-Strong Generalization via Direct On-Policy Distillation", "url": "https://arxiv.org/abs/2607.05394v1", "source_name": null, "published_at": null, "summary": "Direct-OPD reuses a small model's RL run to improve a bigger one: the pre/post-RL log-ratio becomes a dense reward for the stronger student, lifting Qwen3-1.7B from 48.3% to 62.4% on AIME 2024 in 4 hours on 8 A100s." }, { "title": "DemoPSD: Disagreement-Modulated Policy Self-Distillation", "url": "https://arxiv.org/abs/2607.02502v1", "source_name": null, "published_at": null, "summary": "DemoPSD gates self-distillation per token by teacher–student disagreement, cutting the answer-leakage shortcuts that hurt generalization; beats GRPO and SDPO on science QA in and out of domain." }, { "title": "Reasoning LLM Improves Speaker Recognition in Long-form TV Dramas", "url": "https://arxiv.org/abs/2607.02504v1", "source_name": null, "published_at": null, "summary": "DramaSR-532K benchmarks speaker attribution over 532K dialogue lines and 900+ TV-drama characters; a reasoning LLM with multimodal tool use beats acoustic baselines, especially on short utterances." }, { "title": "ReContext: Recursive Evidence Replay as LLM Harness for Long-Context Reasoning", "url": "https://arxiv.org/abs/2607.02509v1", "source_name": null, "published_at": null, "summary": "ReContext is a training-free harness that replays query-relevant evidence from long inputs before answering, taking the best average rank across 8 long-context benchmarks up to 128K on Qwen3-4B/8B and Llama3-8B." }, { "title": "New research shows how AMIE, our medical AI, could help manage health conditions.", "url": "https://blog.google/innovation-and-ai/models-and-research/google-research/amie-for-disease-management-in-nature/", "source_name": null, "published_at": null, "summary": "Google's AMIE matched 21 primary-care physicians on longitudinal disease management in a blinded Nature study, scoring higher on plan preciseness and guideline alignment. Research-stage, not deployed." }, { "title": "GPT-5.6: Frontier intelligence that scales with your ambition", "url": "https://openai.com/index/gpt-5-6", "source_name": null, "published_at": null, "summary": "OpenAI introduced GPT-5.6 with claims of improved token efficiency and cost-performance, but supplied no measurements or access details for model selection." }, { "title": "Introducing Grok 4.5", "url": "https://cursor.com/blog/grok-4-5", "source_name": null, "published_at": null, "summary": "Grok 4.5 extends Cursor’s model pool to long-running tool work beyond coding, but its CursorBench result is excluded because an earlier Cursor code snapshot entered training." }, { "title": "Grok 4.5 now available on AI Gateway", "url": "https://vercel.com/changelog/grok-4-5-now-available-on-ai-gateway", "source_name": null, "published_at": null, "summary": "Grok 4.5 is available through Vercel AI Gateway with text and image input plus low, medium, and high reasoning settings for tuning speed against depth." } ] }