arXiv:2608. 04804v1 Announce Type: cross Abstract: Frontier language models can resolve repository-level software issues, but each attempt is expensive, and existing routers select a model from the issue text alone.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.
arXiv:2609.15982v1 Announce Type: cross Abstract: Skills extend an LLM agent beyond its parametric knowledge, and the gain they promise rests on picking the right one. Deployed harnesses route by pre...
arXiv:2605.18859v3 Announce Type: replace-cross Abstract: LLM routing matters most in long-horizon applications such as coding agents, deep research systems, and computer-use agents, where a single u...
MARS (Multi-Agent Relay of Specialized LLMs) is a prompt-only framework that assigns specialized LLM agents—each focused on a particular algorithmic domain such as dynamic programming, graphs, or geometry—to collaboratively solve competitive programming problems. Retrieval-augmented generation selects a small team of relevant specialists for each problem, and the agents iteratively refine a C++17 solution through sandboxed testing, passing structured packets between them until a final infrastructure-fixer normalizes the code. On the CodeContests benchmark, MARS achieves a pass rate of 0.624 with Gemma 4, improving over direct prompting by 14.4 percentage points while reducing wall‑clock cost and token‑spend variance compared to CodeSIM.
arXiv:2607. 19338v1 Announce Type: new Abstract: Coding agents increasingly operate in executable environments where a failed attempt produces actionable feedback rather than merely an incorrect answer.
arXiv:2609.26086v1 Announce Type: new Abstract: An agentic retrieval system issues a sequence of search queries and must decide, at each step, whether the evidence collected so far is enough to stop....
arXiv:2607. 07946v1 Announce Type: cross Abstract: DeepSWE is a benchmark of 113 original, long-horizon software engineering tasks for evaluating coding agents.