AI Explained
Plain explanations of trending AI concepts, with live visualizations.
Omnigent open-sources a meta-harness for coding agents — The agent meta-harness — What does it mean?
A meta-harness is one control layer above many coding-agent CLIs — it holds credentials, session, policy, and sandbox in one place.
LangChain adds dynamic subagents for code-driven orchestration — Programmatic subagent fan-out — What does it mean?
LangChain Deep Agents can now write a short script that fans out one subagent per chunk, so coverage is a property of code, not a prompt.
HaloGuard ships 0.8B open constitutional safety classifier — Paired counterfactual safety data — What does it mean?
HaloGuard trains a tiny safety classifier on matched prompt pairs that flip only intent, so it learns the boundary, not the keywords.
CheckRLM corrects factual drift inside retrieval-augmented reasoning — In-chain retrieval fact-checking — What does it mean?
CheckRLM fact-checks each claim inside a reasoning model's chain of thought against retrieved evidence, then patches only the wrong step.
SkillCoach self-evolves rubrics to grade agentic skill-use at scale — Self-evolving rubrics — What does it mean?
SkillCoach grades how an agent uses its skills on four axes — with a rubric that rewrites its own criteria, keeping only edits that still grade trusted samples right.
kNNGuard turns LLM hidden activations into a training-free guardrail — Training-free activation-space kNN guardrail — What does it mean?
A guardrail that flags unsafe prompts by reading a frozen LLM's hidden activations and kNN-matching a 50-prompt bank — no training, up to 10× faster.
AgenticSTS tests long-horizon agent memory — Bounded-memory contract via typed retrieval — What does it mean?
AgenticSTS reframes agent memory as a contract — each decision sees only what typed retrieval hands it, so the prompt stays bounded and each memory layer is testable.
TRIAGE cuts agent turns up to 14.8% — Role-typed credit assignment — What does it mean?
TRIAGE grades each agent action by its role — progress, probe, stall, or blunder — not just the final win, so RL wastes fewer turns.
SkillHone evolves agent skills across sessions — Persistent decision-history memory — What does it mean?
SkillHone improves an agent's skills across sessions from an external decision history it reads — no retraining, no weight changes.
QVal: training-free testbed finds prompting beats dense agent supervision — Q-aligned dense supervision — What does it mean?
QVal tests, with no training, whether an agent's per-step supervision ranks actions like a reference policy's Q-values — and finds prompting beats 21 methods.
Dockerless verifies coding-agent patches without containers — Execution-free patch verification — What does it mean?
Dockerless judges whether a coding agent's patch is correct by exploring the repo and reasoning about it, no Docker tests — 62.0% on SWE-bench Verified.
OSWorld2.0 benchmark: best computer-use agent finishes just 20.6% of tasks — Long-horizon computer-use failure modes — What does it mean?
OSWorld2.0 runs computer-use agents through 108 long real-world tasks. The best finishes just 20.6%, undone by four failure modes.
