1.4 KiB
1.4 KiB
Paper: Agentic Retrieval and Reinforcement Learned Equation Chains: A Controlled Generation Framework for Complex and Novel Physics Word Problems
type: paper title: "Agentic Retrieval and Reinforcement Learned Equation Chains: A Controlled Generation Framework for Complex and Novel Physics Word Problems" authors: Tirthankar Mittra year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.15591 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-14 updated_at: 2026-06-14 status: queued relevance: high topics:
- agent-evaluation
- computer-use
- rag methods:
benchmarks:
models:
datasets:
- cs.AI
- cs.CL
- cs.MA related_concepts:
related_jobs:
related_experiments:
related_projects:
collection_score: 14 collection_queries: rag-agent
One-line Takeaway
Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
Why Collected
- matched queries: rag-agent
- inferred topics: agent-evaluation, computer-use, rag
- arXiv categories: cs.AI, cs.CL, cs.MA
- collection score: 14
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
queuedtoskimmedorsummarized?