VOL. 006
8 research signalsDAILY EDITION / SAVED SNAPSHOT
A dated Agentic RL Daily snapshot with 8 verified primary-source signals across papers, official releases, deployment evidence, and safety or alignment findings.
EDITOR'S VIEW
FULL EDITION
Archived / 2026-07-22
01
CodeRescue: Budget-Calibrated Recovery Routing for Coding Agents
Coding agents increasingly operate in executable environments where a failed attempt produces actionable feedback rather than merely an incorrect answer.
02
ResearchArena: Evaluating Sabotage and Monitoring in Automated AI R&D
As AI agents begin to automate AI R&D, we need ways to assess whether their outputs are safe to deploy, even when the agents themselves may be untrusted.
03
ABot-World-0: Infinite Interactive World Rollout on a Single Desktop GPU
We present ABot-World-0, an action-conditioned video world model for real-time, long-horizon closed-loop interaction, supported by a multi-source data infrastructure spanning AAA games, simulation engines, and internet videos to learn controllable world dynamics.
04
alibaba/ROLL v0.3.0
ROLL发布了v0.3.0版本，新增Video RLVR、AgentRunner 2.0、MTP训练、Router Replay、Multi-Teacher OPD等重要特性。
05
Supra Cognitive Modes: A Routed Architecture for Agent Memory
Agent-memory workloads mix direct factual lookup, relation-chain and current-state reasoning, and broad synthesis over long histories.
06
Agents in the Wild: Where Research Meets Deployment
Agentic systems large language model (LLM) based architectures capable of reasoning, planning, acting, and coordinating with tools and other agents are rapidly transitioning from research prototypes to production scale deployments across domains such as software engineering, scientific discovery, and more.
07
They'll Verify. They Just Won't Act. How Authority Framing and Laundered Code Turn a Trusted Agentic CI/CD Pipeline Into an Attack Surface
We study a five-agent CI/CD pipeline (triage -> developer -> security-scan -> review -> approve/deploy), built from five distinct production LLMs across three providers, behind an LLM firewall in shadow mode.
08
Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents
Real-to-sim conversion for robotic interaction with objects remains labor-intensive because it requires more than visual reconstruction: a streamlined real2sim process must recover scene geometries and object states, infer physical parameters, and assemble actors, objects, cameras, poses, and trajectories.