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MM-ToolSandBox: A Unified Framework for Evaluating Visual Tool-Calling Agents
Researchers introduce MM-ToolSandBox, a new evaluation framework for visual tool-calling agents. This framework supports over 500 tools across 16 application domains and can handle multi-image, multi-turn tasks with…
Omni-Decision: A Progressive Evidence-State Agent System for Omni-Modal QA
The paper introduces Omni-Decision, a training-free system designed to answer questions across multiple modalities such as videos, audio, images, web pages, and computation results. It focuses on maintaining a…
Playful AI in Professional Email: A Field Experiment on Tone and Recipient Engagement
A study found that using a large language model (GPT-5) to write work emails in a playful tone increased emotional positivity in recipients, while using a professional tone decreased it. However, neither condition…
Proxy Exploration and Reusable Guidance: A Modular LLM Post-Training Paradigm via Proxy-Guided Update Signals
The researchers propose a new method called Proxy-guided Update Signal Transfer (PUST) for improving the domain-specific capabilities of large language models (LLMs). Instead of using the primary model for exploration…
Reproducing human biases in route choice using large language models: Toward scalable behavioral modeling
This research explores the ability of large language models (LLMs) to reproduce human biases in route choice decisions, traditionally described using Cumulative Prospect Theory (CPT). The study finds that LLMs can…
StoryTeller: Training-Free Narrative Grounding for Long-Form Audio Description
The authors propose a new framework called StoryTeller for long-form audio description (AD). Unlike modern video-language models, StoryTeller maintains a narrative memory that carries forward story-relevant information…
StructAgent: Harness Long-horizon Digital Agents with Unified Causal Structure
In this paper, researchers introduce StructAgent, a framework designed to improve long-horizon digital agents' performance in tasks with evolving contexts and complex workflows. The framework introduces a unified state…
Technical Report on the CVPR 2026@AdvML Workshop Challenge
This text is about the CVPR 2026@AdvML Workshop Challenge which focuses on testing the robustness of vision-language agents (VLAs) used in autonomous driving. The challenge involved creating adversarial images and…
Vinci2: Providing Proactive Assistance in Continuous Egocentric Videos
The text discusses a new proactive assistance system named Vinci2, which provides assistance in continuous egocentric videos by considering the user's history, current activity, and whether help would be welcome. The…
VoxENES 2026: Benchmarking Generalization of Speech Spoofing Detectors Against LLM-Era TTS and Voice Conversion
The paper introduces VoxENES 2026, a new benchmark for testing speech synthesis systems against modern text-to-speech (TTS) and voice conversion (VC) methods. The benchmark includes 53,628 audio samples in English and…
A Practical Investigation of Training-free Relaxed Speculative Decoding
The paper investigates training-free methods to speed up the sampling process of autoregressive Language Models (LLMs) by relaxing some strict guarantees in standard speculative decoding. The authors provide insights…
ADORN: Adaptive Drift handling for Open RAN using Reinforcement Learning
The paper proposes an adaptive retraining method for Open Radio Access Networks (O-RAN) using Reinforcement Learning (RL). The goal is to balance forecasting accuracy and retraining cost in the presence of dynamic…
AI-guided stimuli discovery and generation to optimize facial emotion perception studies in autism
Researchers have developed a method to create and select facial expressions that enhance differences in emotion perception between autistic and neurotypical adults. This is done by training artificial neural networks…
ArtMine: Discovering and Formalizing Artistic Processes
ArtMine is a framework designed to discover and formalize artistic processes from various historical sources. It uses an abductive agent to infer evidence-based production steps, which are then optimized to generate…
Blind-Spots-Bench: Evaluating Blind Spots in Multimodal Models
Researchers introduce 'blind-spots-bench', a new benchmark to evaluate and expose persistent blind spots in modern AI models, especially those from closed-source providers, which can outperform open-weight models by up…
Cognitive-structured Multimodal Agent for Multimodal Understanding, Generation, and Editing
Researchers propose a new model called the Cognitive-structured Multimodal Agent. This agent is designed to understand and generate multimodal data (vision and language) in long-horizon dialogues more efficiently. It…
CommuniWave:A Machine Learning Model for Quantifying the Degree of Temporary Informal Behavior in Urban Communities
Researchers have developed a machine learning model called CommuniWave to help urban managers measure the degree of informal behavior in urban communities. This can help make better decisions for community planning and…
Dimensionality Reduction Meets Network Science: Sensemaking on UMAP's kNN Graph
The authors of the paper 'Dimensionality Reduction Meets Network Science: Sensemaking on UMAP's kNN Graph', published in 2026, discuss a new approach to utilizing the internal k-nearest-neighbor (kNN) graph constructed…
DocMaster: A Hierarchical Structure-Aware System for Document Analysis
DocMaster is a system that allows for the analysis of complex documents while preserving their hierarchical structures such as sections, tables, figures, and equations. It offers an interactive web interface where…
DrugGen 2: A disease-aware language model for enhancing drug discovery
A new generative model called DrugGen-2 has been developed to enhance drug discovery. It takes into account both disease ontology and target protein sequences, improving upon existing models in generating unique…
Formal Mechanisms for Market Stability in Self-Interested Agent Societies: A Marketplace Simulation Study
The study investigates mechanisms to maintain market stability in societies of self-interested agents who tend to defect in repeated social dilemmas. The research uses a multi-agent marketplace simulation with 18 LLM…
From Legacy Documentation to OSCAL: An MCP-Based Agent Pipeline for Threat-Informed Continuous Compliance in Critical Infrastructure
The paper proposes an agent pipeline using Machine Comprehension Powered (MCP) technology to convert natural language system descriptions into audit-ready artifacts in OSCAL format for continuous automated compliance…
Game Theory Driven Multi-Agent Framework Mitigates Language Model Hallucination
Researchers present G-Frame, an adaptive multi-agent framework that reduces hallucinations in lightweight large language models used in rule-based scientific domains. The framework is based on Bayesian and team game…
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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