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The Verification Horizon: No Silver Bullet for Coding Agent Rewards

BACKGROUND
3 SIGNALSFIRST DETECTED 26 June 2026
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How the story developed
11 Sept
10 Sept
26 Jun
Other feeds and industry voices
23 Mar
Stepwise: Neuro-Symbolic Proof Search for Automated Systems Verification

arXiv:2603.19715v1 Announce Type: new Abstract: Formal verification via interactive theorem proving is increasingly used to ensure the correctness of critical systems, yet

REPORT · HOW · ArXiv CS.AIOPEN STORY
13 May
The Evaluation Differential: When Frontier AI Models Recognise They Are Being Tested

arXiv:2605.11496v1 Announce Type: new Abstract: Recent published evidence from frontier laboratories shows that contemporary AI models can recognise evaluation contexts, latently

REPORT · WHEN · ArXiv CS.AIOPEN STORY
6 Oct
Teaching Agents to Code Reliably

arXiv:2610.03984v1 Announce Type: new Abstract: Autonomous coding agents solve repository issues by reading code, running commands, editing files, and submitting patches. Extra

REPORT · WHEN · ArXiv CS.AIOPEN STORY
2 May
In-Context Prompting Obsoletes Agent Orchestration for Procedural Tasks

arXiv:2604.27891v1 Announce Type: new Abstract: Agent orchestration frameworks -- LangGraph, CrewAI, Google ADK, OpenAI Agents SDK, and others -- place an external orchestrator

REPORT · WHAT · ArXiv CS.AIOPEN STORY
19 Jun
Think Again or Think Longer? Selective Verification for Budget-Aware Reasoning

arXiv:2606.19808v1 Announce Type: new Abstract: Test-time reasoning is increasingly used as a serving-time control knob, but extra reasoning is not uniformly valuable: it can

REPORT · WHAT · ArXiv CS.AIOPEN STORY
17 Oct
ClaimScope: Label-Blind Witness Verification for Mathematical Claim Auditing

arXiv:2610.21581v1 Announce Type: new Abstract: Mathematical agents are commonly evaluated by answer accuracy or proof acceptance. We introduce ClaimScope, a 72-task benchmark for

REPORT · WHAT · ArXiv CS.AIOPEN STORY
6 May
Segment-Aligned Policy Optimization for Multi-Modal Reasoning

arXiv:2605.01327v1 Announce Type: new Abstract: Existing reinforcement learning approaches for Large Language Models typically perform policy optimization at the granularity of

REPORT · WHAT · ArXiv CS.AIOPEN STORY
9 Apr
Scaling Coding Agents via Atomic Skills

arXiv:2604.05013v1 Announce Type: cross Abstract: Current LLM coding agents are predominantly trained on composite benchmarks (e.g., bug fixing), which often leads to

REPORT · HOW · ArXiv CS.AIOPEN STORY
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