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The Physics of Multi-Turn Long-Horizon Planning: From Pre-training to Post-training via Single- and Multi-Teacher On-Policy Agentic Distillation
The paper focuses on improving the multi-turn long-horizon planning for foundation model agents. The authors introduce a controlled environment to study the acquisition, shaping, and integration of planning abilities…
GRADRAG: Cross-Component Prompt Adaptation for Coordinated Multi-Agent RAG
The paper introduces GRADRAG, a framework for improving Retrieval-Augmented Generation (RAG) systems by coordinating improvements across different components of the pipeline. It uses feedback from an Evaluator to…
ICAE-Bench: Evaluating Coding Agents as Interactive Project Builders
The paper introduces a new benchmark called ICAE-Bench for evaluating coding agents in interactive project building settings. This benchmark aims to test the ability of agents to transform incomplete product intent…
Toward Continuous Assurance for the Democratization of AI Agent Creation in Industry
The paper proposes a solution to ensure reliability in AI agents created by non-engineering users within organizations, through democratized low-code, no-code, and conversational development environments. The proposed…
Antigen-specific Antibody Multi-modal Foundation Model for Functional Antibody Design
Researchers introduce a new model called AAMFM (Antigen-specific Antibody Multimodal Foundation Model) for designing functional antibodies. The model learns unified representations of antibody sequences and structures…
Adaptive Adversaries: A Multi-Turn, Multi-LLM Benchmark for LLM Agent Security
The paper presents a new benchmark for testing the security of LLM (Language Model) agents against adaptive adversaries in multi-turn interactions. The benchmark, called Adaptive Adversaries, evaluates how defenders…
O-VAD: Industrial Video Anomaly Detection through Object-Centric Tracking and Reasoning
Researchers have developed a new method for detecting abnormal objects and events in industrial settings using an object-centric tracking and reasoning approach. This method is designed to overcome the limitations of…
WorldCupArena: Fine-Grained Evaluation of Language Models and Deep-Research Agents on Football Forecasting
The paper introduces WorldCupArena, a dynamic benchmark for evaluating language models and deep-research agents in predicting football matches. The 2026 FIFA World Cup was its first evaluation, with systems receiving…
Beyond Success Rate: Cost-Aware Evaluation of Offensive and Defensive Security Agents
The researchers evaluate the performance of language model security agents, focusing on costs rather than just success rates. They use offensive Cybench challenges and defensive Splunk BOTS v1 investigation challenges…
Beyond Success Rate: Cost-Aware Evaluation of Offensive and Defensive Security Agents
The researchers evaluated language model security agents based on cost efficiency in addition to their success rates, focusing on offensive CTF challenges and defensive Splunk BOTS v1 investigation challenges. They…
In-Place Tokenizer Expansion for Pre-trained LLMs
Researchers have developed an in-place method called Tokenizer Expansion to upgrade a pre-trained model's tokenizer when language priorities shift, focusing on improving efficiency for users of languages added later…
MedFailBench: A Clinician-Built Open-Source Benchmark for Medical AI Safety Boundary Inspection
The research paper introduces MedFailBench, an open-source benchmark for evaluating the safety of medical AI systems. The benchmark is designed by clinicians and focuses on identifying which safety boundary a system…
MM-IssueLoc: A Controlled Benchmark for Evaluating Visual Evidence in Multimodal Repository-Level Issue Localization
The paper introduces MM-IssueLoc, a new benchmark and evaluation protocol for repository-level issue localization with visual evidence. The benchmark contains over 650 issue-PR instances across multiple languages…
OmniaBench: Benchmarking General AI Agents Across Diverse Scenarios
A research paper titled 'OmniaBench: Benchmarking General AI Agents Across Diverse Scenarios' introduces a new benchmark called OmniaBench, designed to evaluate the capabilities of general AI agents in diverse…
Plover: Steering GUI Agents through Plan-Centric Interaction
The paper introduces Plover, a plan-centric GUI automation system designed to overcome challenges in real-world environments. It allows users to supervise, correct, and inspect the system's behavior by externalizing…
SciDiagramEdit: Learning to Edit Scientific Diagrams from Paper Revisions
The text is about a new system called SciDiagramEdit that automates the editing of scientific diagrams in research papers based on natural language instructions. The system learns from revisions made to figures in…
StructureClaw: Traceable LLM Agents and an Executable Benchmark for Structural Engineering Workflows
Researchers have developed StructureClaw, an artifact-centered workbench that uses LLM (Language Model) agents to operate through governed engineering skills and checks for completion, consistency, and execution of…
Rethinking Penetration Testing for AI-Enabled Systems: From Resource Compromise to Behavioral Objective Violation
The authors propose a new approach to penetration testing for AI-enabled systems. Instead of focusing on direct compromises of infrastructure, they suggest evaluating if adversaries can manipulate system behavior…
OOD-RL-Bench: A Benchmark Framework for Out-of-Distribution Detection in Reinforcement Learning
The paper introduces OOD-RL-Bench, a new framework for testing out-of-distribution (OOD) detection in reinforcement learning (RL). The framework is designed to evaluate the performance of detectors against various…
Heuristic Learning for Active Flow Control Using Coding Agents
A new method for active flow control is proposed in this research paper. Instead of optimizing neural network parameters, the authors use coding agents to search directly for explicit executable feedback laws. The…
Omni-Decision: A Progressive Evidence-State Agent System for Omni-Modal QA
The paper introduces Omni-Decision, a system aimed at answering questions where evidence is spread across multiple modalities like videos, audio, images, web pages, and computation results. The system maintains a…
From Legacy Documentation to OSCAL: An MCP-Based Agent Pipeline for Threat-Informed Continuous Compliance in Critical Infrastructure
The paper proposes an agent pipeline that converts natural language system descriptions into OSCAL format for continuous automated compliance management in critical infrastructure. The pipeline uses MCP-grounded…
Game Theory Driven Multi-Agent Framework Mitigates Language Model Hallucination
Researchers have developed a new framework called G-Frame that helps lightweight Large Language Models perform better in rule-based scientific domains by reducing hallucinations. They created a new model called…
GitLake: Git-for-data for the agentic lakehouse
The authors present GitLake, a Git-based data system for an agent-first lakehouse. It allows agents to work on isolated branches while humans review and publish changes. Pipelines run on temporary branches and are…
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