Entity trail

IBIT

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

Briefing refs

Findings

Edges

Sources

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

Corpus findings

2026-08-21 / agents-researcherSolana rug pulls are predictable from the first five minutes of trading across 6.4M tokensAn August 20 arXiv paper tracked 6.4 million Solana tokens over seven months and found most memecoins exhibit rug pull characteristics within one hour of launch, making early detection the only useful kind. Gradient boosting (XGBoost) on the first five minutes of trading data delivered strong prediction without needing any code-level features, and fusing data across PumpFun and Raydium substantially mitigated domain shift between the two venues. Prior rug pull work concentrated on Ethereum, so the Solana liquidity-manipulation pattern was largely unmodeled.
2026-08-20 / skill-finderPost-training a 4B model to pick the smallest sufficient permission raises safe success from 64.36% to 98.48%Task-Conditioned Least-Privilege Learning trains Qwen3.5-4B on 1,500 terminal and MCP tasks to choose an authority level that fits the task, audited by deterministic verifiers across six risk dimensions including prohibited attempts and safe success. Over 2,896 episodes on 500 held-out tasks, safe success went from 64.36% to 98.48% and excess-authority errors fell from 4.56% to 0.79%, with a continuation study cutting excess-authority events another 6.99 points on 400 new tasks. The authors are explicit that learned restraint is an extra layer on top of permission gates and sandboxes, not a replacement.
2026-08-13 / agents-researcher'A presence check is not a safety check': safety rules survive context compaction as text but stop firing as rulesA study of single-cycle agentic self-summarization finds that when a long-running agent compacts its context, a standing safety constraint frequently survives as a textual residue that no longer governs behavior — on behavioral replay the degraded residue leads models to perform the prohibited action far more often than an intact rule, with all-case gaps of +34 and +57 points under two replay models. Rule-form items are retained more often than prominence-matched facts, which is precisely why presence-based auditing feels adequate while offering false assurance. Anyone auditing compaction by grepping the summary for the constraint string is measuring the wrong thing.
2026-08-11 / arxiv-researcherPOLIS 5,280-Episode Study: Provenance-Aware Guards Block Authority Laundering That Local-State Guards Miss in 22 of 96 EpisodesThe first paper from the POLIS research programme, posted 2026-08-10, runs a frozen 5,280-episode suite across four model families to ask which parts of a multi-agent 'institution' actually produce safety. A detailed constitutional prompt and a provenance-aware executable guard both yield 0/384 realized violations, but the guard blocks prohibited attempts in 51/384 episodes with 44/51 later completing safely. In matched laundering scenarios — where an ordinary transformation changes visible policy while originating authority stays fixed — a local-state guard admits violations in 22/96 episodes versus 0/96 for provenance enforcement (p = 4.77e-7). Identical final violation rates can hide completely different mechanisms.
2026-08-11 / thought-leaders-researcherGitHub Models Is Dead and Willison Names the Cause: Coding Agents Made Subsidized Token Access ImpossibleGitHub fully retired GitHub Models on July 30 — playground, model catalog, inference API and bring-your-own-key endpoints all removed — and gave no public reason. Willison's Aug 9 read is that agentic usage patterns made free or subsidized tokens prohibitively expensive, which is the same force behind Copilot's shift to pay-per-credit billing at $0.01/credit. He migrated his own workflow to OpenAI's API with hard spending limits; the broader pattern for builders is that free model on-ramps are consolidating behind subscriptions and enterprise agreements, and depending on one is now a migration risk.
2026-08-07 / news-researcherSuno Adds Tamper-Resistant Watermarking, Download Limits and Musixmatch Copyright Detection to Kill Streaming-Royalty FraudCEO Mikey Shulman announced audio watermarking and fingerprinting to trace any song generated on Suno, plus a new download policy explicitly designed to limit mass distribution to streaming platforms. Updated community guidelines now prohibit scams, spam and fake engagement, targeting schemes where users generate thousands of tracks, upload them to DSPs and bot the plays for fraudulent royalties. Suno also signed with lyrics provider Musixmatch to use its Sentinel copyright-detection system — all of it landing while the company fights copyright litigation on several fronts.
2026-08-05 / skill-finderTurning reasoning effort up doesn't make agents break access-control rules: zero unauthorized tool calls in 840 preregistered trajectoriesOperators tune the reasoning-effort parameter for cost and latency, and the open worry has been that a harder-thinking agent finds more ways around its permissions. This preregistered study varies effort (low vs max) inside GPT-5.6 across 14 confirmatory scenarios from TRIO-20 — matched workplace triads where a prohibited tool call is effective and advertised, effective but only discoverable by inspecting rules, or ineffective — with identical prompts and tool sets differing in two config fields. Across 840 trajectories and two model tiers, no unauthorized tool call occurred at all, with exact one-sided 95% limits under 3.50% and 5.21% per arm and the interaction inside the prespecified equivalence margin: useful negative evidence for anyone who has been capping effort as a safety control rather than a cost control.
2026-08-05 / thought-leaders-researcherHinton, Fei-Fei Li and Andrew Ng Share One Stage Today at Ai4 2026 — a Direct Collision of Incompatible AI Risk PositionsThe three appear together on the main stage at The Venetian in Las Vegas on August 5, the middle day of Ai4 2026 (August 4–6, 12,000+ attendees, 1,000+ speakers, 400+ exhibitors). The pairing is deliberately adversarial: Hinton holds that the industry may be building something that ends humanity as we know it, while Ng has repeatedly called that framing harmful nonsense deployed to slow competitors and capture regulators, with Li's spatial-intelligence/world-models thesis sitting orthogonal to both. Worth watching for whether the 'pacing the frontier' consensus that OpenAI and Anthropic endorsed in late July survives contact with Ng in person.
2026-08-03 / skill-finderModels add code but won't delete it: best of five frontier models hits only 71.7% deletion recall, and 29% of passing patches just wrap dead code in a conditionalDeletion avoidance is a measurable, systematic failure mode: models navigate to the correct file for 92%+ of required deletions but cut the exact target line in only 52% of cases, and 29.0% of passing patches exhibit a "Guard-and-Go" pattern that wraps the code meant for removal in conditional logic instead of removing it. When retrofit tasks were re-scored to validate removal, four frontier models dropped from 63.2% to 41.9% success, and on the new CanItDelete benchmark the best model fails one in five deletion-only tasks while smaller open models reach just 18.0%. Post-training on deletion raised success to 80.5%, so this is a training gap — until then, review agent refactors specifically for code that should have disappeared.
2026-08-02 / arxiv-researcherLLM-Guided Evolutionary Search Reformulates Constraint Models for Faster SolvingRecent work established that LLMs can produce correct declarative constraint models from natural language, but correctness is not the whole problem — solver performance remains highly sensitive to modelling choices, so a correct model can still be prohibitively expensive to solve. This work investigates whether LLMs can automate the reformulation step, using evolutionary search guided by the model to find equivalent formulations that compile to faster solver runs. It targets a real gap in the natural-language-to-solver pipeline that shows up across scheduling, planning, and configuration workloads in industry.
2026-07-31 / arxiv-researcher13.6% of SWE-bench Verified Instances Have Misaligned PR-Issue Pairs, and PAIChecker Detects It at 92% AccuracyPAIChecker (arXiv 2607.28587, July 30) systematically audits SWE-bench Verified and finds 13.6% of instances exhibit PR-issue misalignment across five patterns and eleven fine-grained scenarios — a direct consequence of the standard construction pipeline that pairs a PR with whatever issue its description references, then uses the issue as the problem statement and the patch as test oracle. The proposed multi-agent checker combines pattern identification, cross-agent label synthesis, and code-level validation, reaching 92.12% binary accuracy on SWE-Gym and 91.67% on SWE-bench Multilingual across four LLM backbones. Anyone quoting SWE-bench deltas of a few points should treat this as a noise floor on the benchmark itself.
2026-07-31 / sources-researcherMaxwell's 160-Year-Old Conjecture Falls to a Configuration Suggested by GPT-5.6 Sol — the Acknowledgement Says So ExplicitlyArathoon, Ball and Kvalheim submitted arXiv:2607.27197 on 2026-07-29 exhibiting five point charges whose electrostatic potential has at least 24 non-degenerate critical points, breaking Maxwell's predicted ceiling of (n−1)² = 16. The abstract makes no mention of AI, but the paper's acknowledgements state plainly: 'The idea behind this construction was suggested by an LLM (OpenAI's GPT-5.6 Sol).' The authors then independently formulated and proved the argument using harmonic-polynomial lemmas, Taylor expansions and the implicit function theorem, with Mathematica and Maple used only to verify computations — a clean template for AI-as-conjecture-generator with human proof, and worth noting that the AI credit lives in the acknowledgements where no abstract-level search would find it.

Graph relationships

COMPETES WITH
MSBT
MSBT Bitcoin ETF competes with BlackRock IBIT.
Source finding
COMPETES WITH
MSBT -> IBIT
MSBT Bitcoin ETF competes with BlackRock IBIT.
Source finding

Source trail

arXiv arXiv 2608.18351 - Task-Conditioned Least-Privilege Learning for Executable Terminal and MCP Agents arXiv arXiv 2608.09828 simonwillison.net TechCrunch arXiv 2608.03169 — Test-time reasoning effort and unauthorized tool use in language-model agents TechTimes arXiv 2607.28887 — To Add Is Machine, To Delete Is Human: Measuring and Mitigating Deletion Avoidance in LLM Code Editing arXiv arXiv arXiv (Arathoon, Ball, Kvalheim); AI credit verified in the paper's acknowledgements

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