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Earlier sources: Artificial Intelligence
Artificial intelligence covers systems that learn from data, generate content, perceive their surroundings, or act toward a goal. Follow model research, agent tooling, evaluation, and the infrastructure used to build and run these systems.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗5995 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- arXiv · Published · First archived
JevVibe: Efficient Classification-Guided Secure Code Generation ↗
Large language models can generate functionally correct code that still contains security weaknesses, motivating repair pipelines that first diagnose a weakness type before deciding how to fix it. The Common Weakness Enumeration (CWE) provides a standardized vocabulary for such diagnoses, but asking an autoregressive language model to generate a CWE label and extracting it from the response raises questions about output validity, speed, and cost, as well as accuracy. We evaluate Jev, a decision model that instead selects directly from a declared set of candidates and returns a probability for…
- GitHub · Repository created · First archived
KickItLikeShika/composimplex ↗
Composable LLM decoding on the probability simplex: library and paper code.
- arXiv · Published · First archived
Audit the Scaffold, Not the Checkpoint: A Stationarity Dichotomy for Recursive Self-Improvement in Agentic Coding ↗
An auditor who checks whether a system's weights are frozen is checking the wrong thing. Our stationarity dichotomy says that iterative self-modification hits strict diminishing returns whenever the agent's reachable set of edits stays fixed, and can escape only if that set expands. Rewriting scaffolding (tools, verifiers, decomposition) expands what an agent reaches without touching a weight, so frozen weights buy an eventual ceiling but no stationarity along the way. The criterion also separates three regimes usually merged: search within a fixed class, test-time training that raises the cei…
- arXiv · Published · First archived
DGF-Bench: A Benchmark for Simulating and Auditing Deception Against Multi-Agent Governance Boards ↗
Tool-using language-model agents can review enterprise projects as governance boards do: they read the evidence, apply written rules and decide whether the project may proceed. Part of that evidence comes from suppliers and project members with a stake in the decision. DGF-Bench is a benchmark in which a board of agents (specialist gates and a General gate that consolidates their decisions) reviews synthetic dossiers while an attacker plants deceptive content in evidence the organization does not vouch for. Dossiers are generated from canonical facts under 61 executable rules, with 42 authorit…
- Hacker News · Posted on Hacker News · First archived
What would a serious AI product look like? ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Who's liable when AI agents go rogue? ↗
Hacker News discussion.
- Hugging Face · Model / dataset date · First archived
aixk/BAAR4-IMG-335M — model update ↗
BAAR4-IMG-335M (Multilingual) 🌐 Official Website: https://baar.uk/model/ 📄 License: Non-Commercial Only (Contact for Commercial Pricing) --- ## 🖼️ Gallery --- ## 📌 Model Overview **BAAR4-IMG-335M-Realistic4** is an ultra-lightweight, **native multilingual text-to-image generation model** engineered with approximately 335M parameters. Built from the ground up for extreme efficiency, this model understands direct prompts across **20 major languages** (Korean, English, German, Spanish, French, Japanese, Chinese, Italian, Dutch, Polish, Portuguese, Russian, Arabic, Bulgarian, Greek, Hindi, Swa
- Hugging Face · Model / dataset date · First archived
User-2468/mini-unet-colorizer — model update ↗
# Mini Photo Colorizer — v3.0 A compact automatic photo colouriser with **3,994,676 learned parameters in total**, including the complete deployed MobileNetV3 encoder. It predicts plausible colours from grayscale photographs. No teacher, critic, external semantic model, retrieval service or ensemble is needed at inference. ## Release contents - `model.safetensors` and `config.json`: the selected checkpoint. - `semantic_model.py`: the complete architecture and strict checkpoint loader. - `inference.py`: Python API and command-line image colourisation. - `colorizer.onnx`: equivalent fixed 256×25
- arXiv · Published · First archived
Fewer Assumptions by Design: A Reusable Skill for LLM-Assisted Verus Verification ↗
LLM-assisted Verus verification is a less tedious method to verify Rust implementations, but paired with self-referential structures, e.g., Doubly Linked Lists (DLLs)ânotoriously difficult to formalise for verificationâit becomes a substantially more demanding verification task. Moreover, a specification weakness can arise when verification relies on unproven or invalidated assumptions, such as axiomatic lemmas and assume statements. We investigate whether LLM agents can synthesize strong DLL specifications while minimizing these trusted base. The analysis follows three different approache…
- GitHub · Repository created · First archived
Alpha-Park/genpark-agent-tool-retry-exponential-backoff-jitter-skill ↗
Fault-tolerant agent tool execution wrapper featuring adaptive exponential backoff, full jitter, rate-limit 429 backpressure handling, and circuit breaker patterns.
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about Artificial Intelligence
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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