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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 ↗5962 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.
- GitHub · Repository created · First archived
reshma-pk/AI-E2EQAWorkflow-Playwright ↗
Open-source repository in JavaScript.
- arXiv · Published · First archived
Hierarchical Frequency-Domain Compression of Implicit Geometric Representations for Large-Scale Point Clouds ↗
Large-scale point cloud representations of complex geome tries incur prohibitive computational and memory costs, necessitating compressed implicit representations. To ad dress this, we propose a unified framework comprising im plicit geometric field representation, hierarchical frequency domain compression, and conditional high-frequency predic tion. Specifically, an unordered point cloud is mapped to an implicit field defined within its physical bounding box. A smooth Fourier pyramid is then constructed, where com pact low-frequency components capture the global geometry. Inter-scale high-fre…
- arXiv · Published · First archived
Getting Motif-ated: Controllable AI Compositions from Injected Motif Prompts ↗
Deep learning has transformed symbolic music generation by borrowing the training paradigms of large language models, with systems such as NotaGen now producing complete, stylistically convincing classical scores from a short prompt. These systems could become powerful creative partners, helping musicians generate endless possibilities. However, current systems expose almost no control handles on the music itself. In principle, control handles could be built into a foundation model trained from scratch, but this is rarely practical without massive amounts of quality annotated data and compute…
- arXiv · Published · First archived
CLAIRE: A Schema-Grounded Hybrid Workflow for Healthcare Administrative Form Completion ↗
Healthcare administrative staff transfer structured information from electronic health records, referrals, claims systems, provider rosters, and work queues into dynamic forms. We developed and evaluated CLAIRE (Clinical Language and Agentic Intelligence for Reasoning and Entry), a hybrid workflow that separates field-state discovery, source-to-field mapping, deterministic validation, bounded correction, escalation, and audit tracing. We tested five synthetic healthcare administrative schemas, 1,000 source records, four interface variants, two data-quality suites, and six comparators, yielding…
- arXiv · Published · First archived
Agentic Network Traffic Monitoring ↗
As the use of agentic artificial intelligence increases in nearly every industry, there exists a widening attack surface. It is necessary to monitor agents to ensure that agents are acting in a way that is aligned with the users intent. Auditing an agent's network traffic provides a clear record of the agent interactions. This work presents a novel approach to monitoring the network traffic of agentic systems using complex valued hypersparse traffic matrices by integrating DBOS (DataBase OS), the OneSparse PostgreSQL database, and the GraphBLAS math library. To develop these concepts an agenti…
- Hacker News · Posted on Hacker News · First archived
We benchmarked our prompt-injection detector against OWASP's LLM Top ↗
Hacker News discussion.
- arXiv · Published · First archived
Forecasting Intraday USD/CAD Exchange Rate with News-Derived Monetary-Policy Signals ↗
Monetary-policy announcements and central-bank communications play a central role in foreign exchange markets, yet their qualitative, unstructured form makes their forecasting value difficult to quantify. While prior research has largely focused on sentiment extracted from financial news, comparatively little is known about the relative contribution of different dimensions of monetary-policy communication. Existing studies primarily evaluate whether textual information improves overall forecasting performance but provide limited insight into which communication channels drive such improvements…
- Hacker News · Posted on Hacker News · First archived
Show HN: A StarCraft BW Arena where LLMs play by writing code ↗
I'm launching StarSkirmish, an arena for LLMs to create StarCraft: Brood War bots It draws on my previous work, LLM Skirmish, where LLMs were asked to write JavaScript strategies to compete in a Screeps like RTS. In StarSkirmish, LLMs get 1 hour of wall clock time to write the strongest StarCraft BW bots they can in C++. It is then evaluated against other LLMs' bots and established human written bots. All bot are BWAPI 4.4.0, played via OpenBW. A…
- Hacker News · Posted on Hacker News · First archived
What Is Jev AI? A Practical Guide to System One and Executable Decisions ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
I run the message board an AI swarm improvised to hack Hugging Face– in the open ↗
Hacker News discussion.
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.
See the collection and counting methodology ↗ · Read the weekly synthesis ↗
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