Every paper checked — nothing hidden

All papers

Every paper checked for brief #4 of 12–19 Oct 2026 — nothing is hidden. Brief papers first.

All17,312 In brief24 More (on-topic)3,333 Not relevant13,753 Not assessed87 Older351 Could not confirm93 Blogs with no paper266 All blogs284

Paper	Topic	Relevance
OpenGCUA: Toward a Fully Open Stack for Generalist Computer Use The paper introduces an open-source framework and codebase for building generalist computer-use agents that operate across visual and code interfaces. In brief · #1New way to see a problemPreprint8/10 suggested	Multimodal models via arxiv · 17 Oct, 06:18	On-topic Builds generalist computer-use agents combining visual interfaces and programmatic execution.
Beyond Downstream QA: Rethinking How We Evaluate Agent Memory The paper presents a benchmark that isolates agent memory evolution from downstream retrieval and generation failures. In brief · #1Surprising resultPreprint8/10 suggested	Retrieval-augmented generation (RAG) via arxiv · 17 Oct, 06:17	On-topic Addresses memory retrieval and ingestion quality across evolving multi-author documents.
Robust Logical Anomaly Detection under Capture Shifts via Synthetic Anomalies Examines industrial logical anomaly detection under capture shifts and proposes a reference-free classifier trained on synthetic anomalies. In brief · #1Surprising resultPreprint8/10 suggested	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	On-topic Focuses directly on robust logical anomaly detection under shift for industrial inspection benchmarks.
AgentSWE: Can Coding Agents Build the Agent You Actually Want? Introduces AgentSWE, a 25-task benchmark evaluating whether coding agents can build, edit, and optimize other software agents against user requirements. In brief · #1Surprising resultPreprint9/10 suggested	AI agents via arxiv · 12 Oct, 16:28	On-topic Evaluates coding agents building and editing complete autonomous agent workflows over multi-step tasks.
VisualTrust: Video Reasoning under On-Screen Claim Framing Introduces a counterfactual benchmark to evaluate whether multimodal models erroneously defer to misleading on-screen text over video evidence. In brief · #2Surprising resultPreprint8/10 suggested	Multimodal models via arxiv · 17 Oct, 06:18	On-topic Evaluates video-language models on text-video conflict and multimodal reasoning.
Copying Is Not Grounding: Training Faithful Long-Form RAG with Authored-Sentence Credit Identifies passage copying as a failure mode in long-form retrieval systems and introduces sentence-level credit assignment to encourage genuine grounding. In brief · #2Surprising resultPreprint8/10 suggested	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:17	On-topic Investigates grounding versus copying in long-form RAG, introducing sentence-level credit training.
Last Secure Code Benchmark: Is the Code You Vibe Secure? This paper introduces a benchmark evaluating whether coding agents produce functionally correct code that also avoids real-world security vulnerabilities. In brief · #2Surprising resultPreprint9/10 suggested	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	On-topic Introduces a benchmark evaluating the security and functionality of code generated by models.
TurnCost: Turns, Not Observations: Cache-Aware Loop Engineering for Coding Agents Analyzes coding-agent trajectories to model execution costs under prompt caching, showing turn count matters far more than observation token length. In brief · #2Surprising resultPeer-reviewed8/10 suggested	Small and efficient models via arxiv · 15 Oct, 06:17	On-topic Evaluates prefix caching, observation compression, and model delegation costs for efficient serving.
Is In-Domain Training Enough for Fine-Grained Industrial Anomaly Understanding? Proposes a multi-agent framework combining general multimodal models with specialized visual experts for industrial defect detection and localization. In brief · #2Surprising resultPreprint8/10 suggested	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	On-topic Addresses multimodal defect detection and industrial anomaly understanding in manufacturing.
SWE-Duel: Towards a Self-Scaling Arena for Coding Agents Presents an arena benchmark where pairs of coding agents dynamically generate, test, and debug code against each other. In brief · #2New testPreprint9/10 suggested	AI agents via arxiv · 12 Oct, 16:28	On-topic Evaluates multi-step coding agents interacting autonomously in an adversarial arena setup.
My Credentials, Please: Detecting Filesystem Capability Laundering in MCP Servers at Scale Analyzes filesystem privilege escalation vulnerabilities in Model Context Protocol servers and develops a tool to detect them. In brief · #3Surprising resultPreprint9/10 suggested	AI safety and reliability in deployment via arxiv · 17 Oct, 06:17	On-topic Investigates security vulnerabilities and privilege laundering in tool-calling agent servers.
What You Sign Is Not What You Run: The Verifiability Gap in Quantized LLM Supply Chains This paper examines the verifiability gap in quantized model supply chains, showing that common GGUF artifacts lack necessary build environment disclosures. In brief · #3Surprising resultPreprint8/10 suggested	Small and efficient models via arxiv · 15 Oct, 15:06	On-topic Examines reproducibility and verifiability gaps in quantized GGUF LLM deployment pipelines.
More Methods, Better Agents? A Reality Check on Self-Distillation in Agentic Reinforcement Learning The paper benchmarks ten self-distillation methods in agentic reinforcement learning across varied model sizes, tasks, and computational costs. In brief · #3Surprising resultPreprint8/10 suggested	AI agents via arxiv · 15 Oct, 15:06	On-topic Benchmarking self-distillation and RL algorithms across multiple agentic task environments.
SWEeper-Bench: Can Agents Discover Bugs in Interactive Software? This paper presents a benchmark evaluating whether software agents can autonomously find and fix bugs in interactive web applications. In brief · #3New testPeer-reviewed8/10 suggested	LLMs for code via arxiv · 15 Oct, 06:19	On-topic Introduces a benchmark evaluating coding agents on finding and fixing software bugs.
Welcome to the Age of Agent Ads: Using On-Policy Attacks to Steer Agentic Decisions The paper investigates on-policy indirect manipulation attacks that steer autonomous agent purchasing and ranking decisions via web retrieval. In brief · #3Surprising resultPreprint8/10 suggested	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:17	On-topic Analyzes how adversarial web search results poison agent grounding and option ranking.
Right Screen, Wrong Transition: World Models as Verifiers for GUI Agents The paper introduces LGWM, an action-conditioned world model predicting next-screen latent representations to verify GUI agent state transitions. In brief · #3Surprising resultPreprint8/10 suggested	Multimodal models via arxiv · 12 Oct, 16:28	On-topic Evaluates visual state transitions for GUI agents using visual screen representations.
A Real-World CAD Segmentation Benchmark: Comparing Rule-Based and Learning-Based Approaches through Hole Detection Introduces a real-world CAD segmentation benchmark focused on fastener hole detection, comparing rule-based approaches with deep learning methods. In brief · #3New testPreprint7/10 suggested	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	On-topic Introduces a real-world CAD segmentation and hole detection benchmark for engineering tasks.
Facts Don't Speak Louder than Words: The Behavioral Essence of Long-CoT Distillation The paper studies long chain-of-thought distillation and argues improvements stem from structured reasoning patterns rather than factual correctness. In brief · #4Surprising resultPreprint8/10 suggested	Small and efficient models via arxiv · 15 Oct, 06:17	On-topic Investigates the mechanics of reasoning distillation to make reasoning models smaller and more efficient.
SWE-MISBEHAVIOR: Benchmarking and Mitigating Boundary Violations in Software Coding Agents Introduces a benchmark evaluating coding agent misbehaviors across code generation, file management, and system environment integrity. In brief · #4New testPreprint8/10 suggested	LLMs for code via arxiv · 15 Oct, 06:17	On-topic Benchmarks misbehaviors and mitigation strategies in software engineering agents.
Athanor: An Agent-Native System for Autonomous Post-Training Research Develops an open agent environment for evaluating how autonomously language agents can conduct post-training machine learning experiments. In brief · #5Surprising resultPreprint8/10 suggested	LLMs for code via arxiv · 17 Oct, 06:17	On-topic Agents autonomously write, modify, and debug machine learning training scripts and code.
The Thinking Leakage in Reinforcement Learning for LLMs The paper examines whether non-thinking mode reinforcement learning gains in hybrid reasoning models stem from leakage of thinking-mode activations. In brief · #5Surprising resultPreprint8/10 suggested	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	On-topic Demonstrates evaluation confounds where RL gains stem from internal mode shifts.
APEX-Harm: Evaluating Agent Safety in Shared Professional Workspaces The paper introduces a benchmark evaluating agent susceptibility to prompt and script injections across multi-tool shared workspace environments. In brief · #6New testPreprint8/10 suggested	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:28	On-topic Introduces APEX-Harm, a benchmark evaluating prompt and script injection against frontier models.
The Agent Knew: Internal States Forecast Unauthorized Actions and Stop Them, and the Lies That Follow The paper demonstrates that internal activation states can forecast and block unauthorized actions and deceptive reports by language model agents. In brief · #8Surprising resultPreprint8/10 suggested	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	On-topic Investigates detecting and stopping unauthorized actions and deceptive reports in agents.
Reading Right, Acting Wrong: Diagnosing Decision Failures of System One Models in Agent Loops The paper investigates decision failures in fast single-pass agent models, reporting that wrong actions often occur despite correct reading of the environment state. In brief · #9Surprising resultPreprint8/10 suggested	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	On-topic Diagnoses reliability and decision failures in deployed LLM agent loops.

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