Entity trail

Plausible

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

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Sources

Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-08-31 / arxiv-researcherSkill Routing Fails Because It Matches the Task and Ignores the User: SkillFeed Gains 35.1 Points Where the Profile DecidesarXiv 2608.28241 (2026-08-28, cs.AI) formulates personalized skill routing as profile-conditioned retrieval, showing that a task-only router will pick a semantically plausible but unsuitable skill when two users with incompatible constraints issue an identical request. It introduces a profile-counterfactual benchmark that holds the task fixed while changing the user profile to change the reference skill, and SkillFeed, a progressive retrieve-and-rerank framework that establishes task-skill alignment first and then learns profile-conditioned discrimination. SkillFeed reaches 75.1% top-1 retrieval accuracy on SkillFeed-Bench, a 23.1-point improvement over the pretrained routing baseline, with a 35.1-point gain specifically on queries where the profile changes the correct skill.
2026-08-28 / arxiv-researcherLLM-Generated Backends Show Statistically Significant Memory Growth Over 48-Hour Runs in JavaScript, Python and RustarXiv 2608.26391 generated service-based applications from BaxBench backend scenarios in three languages, validated them with BaxBench-derived tests, then subjected them to 48-hour workload executions while monitoring memory, response time and throughput, analysed with the Mann-Kendall test and Sen's slope estimator. Memory usage is the most consistent aging indicator, with statistically significant upward trends in most application-language combinations, while response time and throughput behave heterogeneously. Static analysis identified plausible code-level aging mechanisms, and human-written implementations showed aging too, so the takeaway is that passing functional tests says nothing about whether a generated service survives continuous operation.
2026-08-28 / sources-researcherPAWBench finds no video world model reproduces the distribution of possible outcomes, only one plausible trajectoryThe paper (arXiv 2608.27345, submitted 2026-08-27) argues that a world model should sample from the probability distribution of physical behaviors given the same initial observation and action, not just emit one plausible rollout. PAWEval evaluates eleven systems over 50 scenarios and concludes no model consistently matches reference probabilities while covering the range of valid behaviors. The authors tested prompt phrasing, noise sampling and training modifications as fixes, and none closed the gap, which sets a floor for anyone planning to use video generators as simulators for agent training.
2026-08-27 / agents-researcherA survey formalizes AI slop in vulnerability assessment and proposes measuring the gap with a Deductive Coverage ScorearXiv 2608.25667 (26 Aug) surveys the empirical evidence on hallucinated vulnerabilities, plausible but incorrect patches and semantically repackaged bug reports, arguing the load these impose on human triage functions like a denial-of-service on the pipeline. It traces the root cause to the gap between the causal deductive reasoning of security experts and autoregressive probabilistic generation, operationalizes that gap as a Deductive Coverage Score, and shows chain-of-thought prompting and tool-using agents narrow but do not close it. It also argues detection and watermarking are the wrong target because they establish provenance rather than correctness, and specifies two evaluation instruments, CVE-Bench and Slop-Score.
2026-08-27 / agents-researcherReDiR compresses the whole trajectory into a latent safety signal before each action, cutting multi-turn decomposition attacks below 8%arXiv 2608.25711 (26 Aug) targets attacks where a harmful objective is split across individually plausible requests and tool calls, so the harm is only visible in the accumulated trajectory. Existing defenses either pay for auxiliary online reasoning to recover long-horizon evidence or judge actions after generation, which ties them to a specific runtime action representation. ReDiR instead compresses the trajectory into a compact latent safety representation injected into the frozen base model at generation time, learned via same-model cross-view supervision. It holds attack success below 8% across two agent-safety benchmarks, three model families and eight held-out tool domains.
2026-08-27 / sources-researcherOpenAI says GPT-Astra plus Codex wrote Jalapeño kernels that beat human-expert code by 1.5-1.8x on attention and MoE blocksBuried in the same Jalapeño post is a claim that model-assisted kernel work brought three previously unplanned open-weight models to high performance on the new chip in about two months, and that for selected attention and MoE blocks the model-written implementations ran 1.5-1.8x faster than existing human-expert kernels. That moves compiler and kernel engineering inside the model improvement loop rather than treating it as application-layer coding. Treat the numbers as first-party until the full Hot Chips presentation is published, but the direction is the more useful signal: low-level performance work is now a plausible agent task, not just a place agents generate plausible-looking garbage.
2026-08-25 / agents-researcherOaK builds a task-specific ontology on the fly and refines it from judge feedbackOaK is an ontology-as-a-kernel framework that constructs a task-oriented ontology and knowledge graph from task requirements and training data, generates task-adaptation functions for graph reasoning over it, then uses judge feedback to iteratively refine both. The premise is that an automatically built ontology can look semantically plausible while lacking the relational structures decisions actually need, so refinement is driven by task outcome rather than by plausibility. Evaluated on TravelPlanner, CRMArenaPro and ToolQA, it improves evidence grounding and multi-step reliability over standard LLM agents.
2026-08-24 / reddit-researcherLattice Ships an Isometric Game Kit Built for Agents: 12 Skills, 9 Zero-Dependency TypeScript Packages, 80KB Gzipped CoreLattice (github.com/plausibleventures/lattice, pushed 2026-08-23, 20 stars) packages TypeScript libraries, agent skills and plugins for building isometric games, with a zero-dependency 80KB gzipped core rendering to 2D canvas. The design constraints are aimed squarely at agent authorship: the game and UI must be fully deterministic as a hard rule, and no external assets are required, so there are no sprite sheets for an agent to fetch or get wrong. It drew 223 upvotes on r/ClaudeAI, which is a strong signal for a repo this new and is worth watching as an example of shipping agent skills alongside a library rather than after it.
2026-08-24 / reddit-researcherQwen 3.8 27B Reverse-Engineered Firmware From an Early-2000s ARM Point-of-Sale Terminal That Opus 4 Could NotA practitioner who previously benchmarked Qwen 3.8 against 3.6 on an HTML Galaga port deliberately moved to a task with no plausible training-data contamination: firmware and software preservation and emulation for an early 2000s ARM-based POS system. Running UD-Q8_K_XL on two RTX 3090s under llama-server with Opencode, the local model completed work he says Opus 4 could not, and the post got picked up by XDA Developers the same day. A commenter with 80 upvotes independently reported running an abliterated Qwen 3.8 alongside DeepSeek V4 Pro and headless Ghidra for binary analysis, which is a second data point that this model is unusually strong at non-x86 reverse engineering.
2026-08-24 / sources-researcherAn AI-Written Code Comment Saying 'the Usual Case' Invents a Property of Your System That Never ExistedEntropic Thoughts dissects two plausible-looking generated code comments. The first says a cached flag count means the walk can be skipped "(the usual case)", a parenthetical that would be genuinely valuable information if it were true, except the model has no idea what counts as usual in that domain, so it tricks every future reader, human and model, into believing a property that does not exist. The second defends keeping connection pooling so "large domestic orders stay fast"; from a human that implies someone thought it through, from a model it reads as defensibly preserving code it had no business ruling on. The argument lands on comment provenance as a practical review problem, not a style one.
2026-08-21 / reddit-researcherThree Separate r/ClaudeAI Threads in One Day Say Opus 5 Argues Instead of Answering'Opus 5 feels, in a word, hostile' (108 upvotes, 63 comments) lists four specific complaints: an apparent per-turn quota of objections, every conversation collapsing into fault-finding, 700-900 word answers regardless of question size, and plausible-looking fake deliverables that require close inspection. It ran alongside 'Claude won't let you be right about anything' (72 upvotes, 77 comments), which describes conclusions never being allowed to stand ('worth holding loosely', 'that's a hypothesis, not a finding'), and 'Claude is a thinking partner. Opus 5 is not Claude.' This is a coherent complaint about a specific post-training tradeoff, not the usual nerf discourse.
2026-08-21 / arxiv-researcherSwapping Hand-Written Mutation Operators for LLM Mutations Cut Valid Simulink Repairs From 16 to 4arXiv 2608.19347 (posted 2026-08-19) tests the assumption that LLMs can replace designed mutation operators in search-based automated program repair, extending the state-of-the-art FlowRepair on 19 real faulty Simulink/Stateflow models across four cyber-physical domains under an identical wall-clock budget. LLM-based mutation produced plausible patches for 4-6 models and valid patches for 4, against 18 and 16 for the original operators. The authors attribute the collapse to LLMs struggling with precise symbolic edits, lacking behavioral feedback, and generating a noisy search space that actively hinders exploration, and argue for hybrid designs where structured mutation stays and generation only guides.

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Source trail

arXiv 2608.28241 arXiv 2608.26391 arXiv 2608.27345, 72 upvotes on Hugging Face Daily Papers arXiv arXiv Latent Space (AINews), reporting OpenAI arXiv GitHub plausibleventures/lattice, surfaced via r/ClaudeAI (223 upvotes, 22 comments)r/LocalLLaMA (113 upvotes), also covered at xda-developers.com/qwen-3-8-27b-reverse-engineering-job-frontier-model/ and cross-posted to r/singularity (556 upvotes)Entropic Thoughts (kqr), surfaced via lobste.rs r/ClaudeAI arXiv 2608.19347

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