Large language model (LLM) agents are increasingly capable of acting in complex tool-use environments, yet they often fail to recognize when tasks are infeasible and no valid solution exists. Recent w
Large language model (LLM) agents are increasingly capable of acting in complex tool-use environments, yet they often fail to recognize when tasks are infeasible and no valid solution exists. Recent w
Details from Hugging Face ↗.
HERA: Harness-Environment Co-Evolution for Reliable Agentic Abstention was first seen on Hugging Face · Daily papers on Oct 21, 2026. Since then it has appeared in 2 checks on 1 different day. Its best position was #22 of 30, reached on Oct 21, 05:18 UTC. It dropped off the list after Oct 21, 05:18 UTC.
This page has little history so far; it stays out of search results until the item has trended on two days or has more context.
Position on Hugging Face · Daily papers at every check (lower is better).
Best rank per day (UTC).
Platform metric as reported by Hugging Face.
Archived daily, weekly and monthly lists that include this entry.
Not at the moment. It was last on the list on Oct 21, 05:18 UTC, after 1 day of trending.
#22 on Hugging Face · Daily papers, on Oct 21, 05:18 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Oct 21, 2026 and has been on the list on 1 day (2 checks) since.