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agent/papers/items/2026-2604-25135-fama-failure-aware-meta-agentic-framework-for-open-source-llms-in-interactive-to.md
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# Paper: FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use Environments
---
type: paper
title: "FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use Environments"
authors: Amir Saeidi, Venkatesh Mishra, Souradeep Mukhopadhyay, Gaowen Liu, Ali Payani, Jayanth Srinivasa, Chitta Baral
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2604.25135
code_url:
source: arxiv
collected_at: 2026-07-08
published_at: 2026-04-28
updated_at: 2026-04-28
status: queued
relevance: high
topics:
- agent-evaluation
- tool-use
methods:
-
benchmarks:
-
models:
-
datasets:
- cs.CL
related_concepts:
-
related_jobs:
-
related_experiments:
-
related_projects:
-
collection_score: 18
collection_queries: autonomous-agent-llm
---
## One-line Takeaway
Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
## Why Collected
- matched queries: autonomous-agent-llm
- inferred topics: agent-evaluation, tool-use
- arXiv categories: cs.CL
- collection score: 18
## Review Checklist
- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
- Does it include a benchmark, dataset, code, or reproducible experimental setup?
- Should it be promoted from `queued` to `skimmed` or `summarized`?
## Links
- arXiv: https://arxiv.org/abs/2604.25135