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Earlier sources: AI agents
AI agents use models to choose actions, call tools, and work toward a goal. This thread follows agent frameworks, memory, orchestration, evaluation, and safeguards; autonomy and reliability vary between 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 ↗852 classified signals in the fourteen-day window. 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
alphaparkinc/genpark-agent-hallucination-fact-verifier-skill ↗
Atomic claim decomposition and cross-context fact verification engine detecting ungrounded claims, numerical contradictions, and hallucinated entities against reference knowledge.
- GitHub · Repository created · First archived
Alpha-Park/genpark-agent-tool-dag-speculative-prefetcher-skill ↗
Topological tool dependency DAG scheduler and speculative prefetcher resolving agent tool execution graphs with parallel batching and speculative argument evaluation.
- Hacker News · Posted on Hacker News · First archived
We found 24 Android vulnerabilities using our open source AI security agent ↗
Hacker News discussion.
- GitHub · Repository created · First archived
alphaparkinc/genpark-agent-tool-dag-speculative-prefetcher-skill ↗
Topological tool dependency DAG scheduler and speculative prefetcher resolving agent tool execution graphs with parallel batching and speculative argument evaluation.
- GitHub · Repository created · First archived
Alpha-Park/genpark-agent-dynamic-few-shot-example-selector-skill ↗
Dynamic few-shot in-context exemplar selector utilizing semantic token overlap, cosine similarity and Maximal Marginal Relevance (MMR) diversity ranking for prompt optimization.
- GitHub · Repository created · First archived
alphaparkinc/genpark-agent-dynamic-few-shot-example-selector-skill ↗
Dynamic few-shot in-context exemplar selector utilizing semantic token overlap, cosine similarity and Maximal Marginal Relevance (MMR) diversity ranking for prompt optimization.
- Hacker News · Posted on Hacker News · First archived
Show HN: Corral – Kill every command your agent starts ↗
This summer I got to intern on the backend of an AI agent and I noticed that it would run commands like tail -f or some random background jobs and exit without terminating any of these. I got curious and looked up how Claude Code handles stuff like this, and it turns out they have similar problems. There are issues about background processes from the Bash tool not getting cleaned up when the session ends, and one where a timeout sends SIGTERM to…
- GitHub · Repository created · First archived
elopstudio/elop-crew ↗
ELOP Crew ? the AI Agent Monitor for Claude Code: a local dashboard and desktop app for every Claude Code session on your machine, grouped as project, leader and agents. Claude Code only, for now.
- OpenAlex · Published · First archived
A Multi-Agent Framework for SQL Injection Auditing with LLM-Driven Post-Exploitation and Privilege Escalation ↗
Web security audits of SQL injection (SQLi) vulnerabilities still depend primarily on the analyst’s skill and knowledge to select the right tools, interpret results, and determine whether there is any vulnerability. This work presents SQLiAgent, an open-source multi-agent framework that automates the complete cycle of an SQLi audit—from initial recognition to post-exploitation assisted by artificial intelligence (AI)—in order to facilitate the detection and subsequent patching of vulnerabilities. SQLiAgent integrates well-established tools from the pentesting ecosystem within a decoupled and t…
- OpenAlex · Published · First archived
OptimAI: Optimization from Natural Language Using LLM-Powered AI Agents ↗
Optimization plays a vital role in scientific research and practical applications. However, translating a concrete optimization problem described in natural language into a mathematical formulation and selecting a suitable solver require substantial domain expertise. We introduce OptimAI, a framework for solving optimization problems described in natural language by leveraging LLM-powered AI agents, and achieve superior performance over current state-of-the-art methods. Our framework is built upon the following key roles: (1) a formulator that translates natural language problem descriptions i…
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about AI agents
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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These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.