Agents
Brilliant paper on scaling research agents from UC Berkeley. (bookmark it) They propose an unexpected and interesting way to scale automated…
Brilliant paper on scaling research agents from UC Berkeley. (bookmark it) They propose an unexpected and interesting way to scale automated research with agents. It's common to see research agents ke
Brilliant paper on scaling research agents from UC Berkeley. (bookmark it) They propose an unexpected and interesting way to scale automated research with agents. It's common to see research agents keep their full history and iterate on it to solve a task. After a while, each agent anchors on its own past attempts, makes smaller edits, and extra budget stops improving things. So this work induces forgetting in the agents. Periodically, they discard each agent's session and the candidate history, and then restart from the best candidate found so far. Across heuristic programming, kernel optimization, and model training tasks, this gives up to 15% over parallel agents and up to 39% over a single agent with the same budget. https://arxiv.org/abs/2610.20563 Chat with Paper: https://academy.dair.ai/papers/scaling-discovery-requires-forgetting-2610.20563
Related
- NEW paper worth reading. (bookmark it) Autonomous research systems usually prove themselves on cherry-picked wins, human-framed topics, or a…
- Banger paper from Meta AI on research agents that decide what to investigate next. (bookmark it) If you run long-horizon research agents, ch…
- Banger paper from BAAI. If you are building research agents, this one is worth your time. (bookmark it) They find that adding skills scores …
- Banger paper from Microsoft Research and colleagues. It studies the potential benefits of agents that share progress while they work. (bookm…
Source: DAIR.AI (X) | 2026-10-16