Search: “framework”

Multimodal Injury Risk Prediction in Tennis

arXiv:2608.25126v1 Announce Type: new Abstract: Machine learning has had a significant positive impact on the prediction of athlete performance and injury risk. Most works in this field rely on subjec

OmniPhys: A Unified Multimodal Benchmark for Physics Understanding and Generation from Chinese Educational Corpora

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DGX agent

arXiv:2608.25398v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong abilities in solving diverse visual and textual reasoning tasks. However, their develo

model-releasesarxiv-cs-cl

27 Aug 2026

Output Dilution: Redundant but Fragile Representations in MoE Models

arXiv:2608.25231v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models appear to encode moral content as robustly as dense models, yet prove far more fragile in their encoding. In OLMoE-1B-

researcharxiv-cs-cl

Phase-Consistent Magnetic Spectral Learning for Multi-View Clustering

arXiv:2602.18728v2 Announce Type: replace-cross Abstract: Unsupervised multi-view clustering (MVC) aims to partition data into meaningful groups by leveraging complementary information from multiple v

safetyarxiv-cs-cv

PonsRAG: A Pons-Inspired RAG Bridging Cognitive Islands for Coordinated Long Narrative Reasoning

arXiv:2608.25486v1 Announce Type: cross Abstract: Long Narrative Reasoning is an essential capability for processing and reasoning over complex narratives. While retrieval-augmented generation provide

researcharxiv-cs-cl

Quantum-Inspired Modeling of Driving Behavior

arXiv:2608.25907v1 Announce Type: new Abstract: Driver behavior is heterogeneous, context-dependent, and changes over time, and these properties shape the traffic phenomena we observe. Most models, ho

agentsarxiv-cs-lg

Recurrence Meets Transformers for Universal Multimodal Retrieval

arXiv:2509.08897v2 Announce Type: replace-cross Abstract: With the rapid advancement of multimodal retrieval and its application in LLMs and multimodal LLMs, increasingly complex retrieval tasks have

researcharxiv-cs-cl

Regularized Latent Dynamics Prediction is a Strong Baseline For Behavioral Foundation Models

arXiv:2603.15857v2 Announce Type: replace-cross Abstract: Behavioral Foundation Models (BFMs) produce agents with the capability to adapt to any unknown reward or task. These methods, however, are onl

Routed Graph Handoff: Adaptive Format Selection for Multi-Agent LLM Delegation

arXiv:2608.25277v1 Announce Type: new Abstract: Multi-agent LLM systems coordinate through natural-language messages that consume 40--60% of their token budget. Replacing these with structured graphs

agentsarxiv-cs-cl

Local Ai

See More, Detect Less? Taming Information Leakage in Multi-View Anomaly Detection

arXiv:2608.25168v1 Announce Type: new Abstract: In multi-view anomaly detection, more cross-view information can actually hurt. When multiple inspection views are naively fused in a reconstruction-bas

local-aiarxiv-cs-cv

Segmentation-Based Attention Entropy: Detecting and Mitigating Object Hallucinations in Large Vision-Language Models

arXiv:2603.16558v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) achieve strong performance on many multimodal tasks, but object hallucinations severely undermine their reliabi

researcharxiv-cs-cv

Semi-Supervised Adaptation of Vision-Language Models for Image Classification

arXiv:2608.25485v1 Announce Type: new Abstract: Vision-language models like CLIP have shown sig- nificant potential in handling natural images, yet their perfor- mance is often limited by the distinct

Sequential Object Placement Optimization with Convex Decomposition

arXiv:2608.25162v1 Announce Type: new Abstract: Robotic object packing has been a core challenge for robotic deployment in logistics, industry, etc., due to the curse of dimensionality in combinatoria

applicationsarxiv-cs-ro

SkyDrive: Learning to Drive in a New City from Aerial Traffic Monitoring

model-releasesarxiv-cs-ro

arXiv:2608.25142v1 Announce Type: new Abstract: Autonomous driving has made remarkable progress through imitation learning with massive human demonstration data. However, a trained planner often degra

SMART: MLLM-guided Temporal Alignment for Unifying Sign Language Recognition and Spotting

arXiv:2608.25493v1 Announce Type: new Abstract: Continuous sign language recognition (CSLR) aims to recognize gloss sequences from unsegmented sign videos under weak sequence-level supervision. Howeve

safetyarxiv-cs-cv

SonicNudge: Controlled Displacement of Hovering UAVs via Estimator-Controller Coupling

arXiv:2608.25319v1 Announce Type: cross Abstract: UAV displacement attacks have traditionally relied on spoofing sensors that directly report position or translational motion, such as GNSS and optical

safetyarxiv-cs-ro

SUPER ODOMETRY 2.0: Resilient Odometry via Hierarchical Adaptation

arXiv:2608.25427v1 Announce Type: new Abstract: Resilient and robust odometry is crucial for autonomous systems operating in complex and dynamic environments. Existing odometry systems often struggle

safetyarxiv-cs-ro

Super Star: Towards Streaming Real-time Interactive Agents for Digital Humans

arXiv:2608.24909v1 Announce Type: cross Abstract: Existing co-speech gesture generation methods are predominantly studied in offline settings, where gestures are synthesized from complete speech segme

agentsarxiv-cs-cv

The coolest part of Microduck might not be the robot. It's how it learns to move. This repo shows the full reinforcement learning pipeline b…

The coolest part of Microduck might not be the robot. It's how it learns to move. This repo shows the full reinforcement learning pipeline behind Microduck. The robot learns in simulation using MuJoCo

safetyclem-delangue--x

Three-Way Open-Set Detection for Robust Autonomous Navigation

arXiv:2511.15343v2 Announce Type: replace Abstract: Autonomous navigation in complex scenes requires reliable perception across scenarios that the model did not encounter during its training. Along it

agentsarxiv-cs-cv

Today, we're kicking off the first phase of the research preview for Model Hardware Standard (MHS): a new standard for AI agents to safely o…

applicationsyohei-nakajima--x

Today, we're kicking off the first phase of the research preview for Model Hardware Standard (MHS): a new standard for AI agents to safely operate physical equipment in scientific research and advance

Towards Fine-Grained Text-to-3D Quality Assessment: A Benchmark and A Two-Stage Rank-Learning Metric

arXiv:2509.23841v3 Announce Type: replace Abstract: Recent advances in Text-to-3D (T23D) generative models have enabled the synthesis of diverse, high-fidelity 3D assets from textual prompts. However,

Local Ai

Trust-Aware Sequential Decision Making and Rollout Planning for Resilient Multi-Robot Systems

arXiv:2608.25690v1 Announce Type: cross Abstract: Sequential decision-making in multi-robot systems typically assumes that planning information is reliable and that agents execute the actions anticipa

local-aiarxiv-cs-ro

TrustFormer: Cross-Temporal and Cross- Dimensional Transformer for Task-Specific Multi-Dimensional Trust Evaluation

arXiv:2608.25238v1 Announce Type: cross Abstract: In dynamic collaborative systems, the selection of reliable collaborators is critical to ensuring effective task execution. Existing trust evaluation

VISA: Agentic Self-Evolving Data Synthesis for Multimodal Instruction Following

arXiv:2608.26013v1 Announce Type: new Abstract: Multimodal instruction-following models require training data that is accurate, diverse, verifiable, and challenging. Existing synthesis pipelines typic

agentsarxiv-cs-cl

VisDocAgentBench: Benchmarking Agents for Visually Rich Document Retrieval

arXiv:2608.17889v1 Announce Type: cross Abstract: Visually rich documents encode relevance through language, layout, structured visual elements, and corpus context, yet retrieval is typically evaluate

When Does Context Routing Help? A Systematic Study of Multi-Modal Fusion in Time Series Forecasting

model-releasesarxiv-cs-lg

arXiv:2608.25128v1 Announce Type: new Abstract: Multi-modal time series forecasting methods integrate auxiliary context into temporal predictions through increasingly sophisticated fusion mechanisms.

Zero-WAM: In-Context World-Action Modeling from Human Videos for Open-Ended Task Generalization

arXiv:2608.26103v1 Announce Type: cross Abstract: Zero-shot cross-task generalization, where a policy must execute manipulation tasks never seen during training, remains a central challenge in robot l

A Geometric Theory of Robust Fairness Audits

model-releasesarxiv-cs-lg

arXiv:2608.24818v1 Announce Type: new Abstract: Neighborhood-based fairness audits evaluate individual fairness by comparing predictions among similar individuals in feature space. Despite their wides

ACE: A Self-Correcting Agentic Canvas Editor for Multi-Slide Presentation Automation

arXiv:2608.24103v1 Announce Type: new Abstract: Commercial design platforms increasingly edit documents through large language model (LLM) agents, but two practical problems block reliable deployment:

Ad Insertion in LLM-Generated Responses

arXiv:2601.19435v2 Announce Type: replace-cross Abstract: Sustainable monetization of large language models (LLMs) remains a critical open challenge. Traditional search advertising, which relies on st

researcharxiv-cs-ai

ADVERSA: Measuring Multi-Turn Guardrail Degradation and Judge Reliability in Large Language Models

arXiv:2603.10068v2 Announce Type: replace-cross Abstract: Most adversarial evaluations of large language model (LLM) safety assess single prompts and report binary pass/fail outcomes, which fails to c

AgentWorld: Personality-Aware Reliability Evaluation for Agentic Information Retrieval

arXiv:2608.24076v1 Announce Type: new Abstract: Evaluation of agentic information retrieval remains limited to scripted interactions with uniform users, missing both natural personality diversity and

agentsarxiv-cs-ai

Anytime Pretraining: Horizon-Free Learning-Rate Schedules with Weight Averaging

arXiv:2602.03702v2 Announce Type: replace-cross Abstract: Large language models are increasingly trained in continual or open-ended settings, where the total training horizon is not known in advance.

AQLoRA: A Zero-Search Recipe for Fast Quantized LoRA Fine-Tuning

arXiv:2608.23816v1 Announce Type: new Abstract: Quantized fine-tuning (QLoRA) saves memory but not time. It dequantizes every 4-bit weight on the fly, so it trains more slowly than fp16 LoRA. We prese

Automatic Model Card Generation Using an LLM

arXiv:2608.24807v1 Announce Type: cross Abstract: Model cards are structured documents that summarize key information about machine learning models to improve transparency, usability, and accountabili

safetyarxiv-cs-ai

Beyond Accuracy: A Dual-Judge Evaluation Protocol for Vision-Language Models in Legally Grounded Tasks

arXiv:2608.24258v1 Announce Type: new Abstract: AI systems are increasingly evaluated for legally accountable settings, where correct outputs must also be justifiable against an applicable legal stand

applicationsarxiv-cs-ai

Beyond Executable Models: The Pufibara Agent Harness and the Modelica Agent Workflow Benchmark for Physical System Modeling

arXiv:2608.23653v1 Announce Type: cross Abstract: AI agents are increasingly used for simulation-driven engineering. Physical system modeling presents different requirements from general-purpose code

Causal Analysis for Time Series Foundation Models

arXiv:2608.24303v1 Announce Type: new Abstract: Transitioning from bespoke time series models towards time series foundation models changes the relationship of model and application from one-to-one to

safetyarxiv-cs-lg

Constrained Entity Selection under Partial Knowledge for LLM-Based Knowledge Graph QA

arXiv:2608.24824v1 Announce Type: new Abstract: Large language models are increasingly used for knowledge graph question answering (KGQA), but can fail to correctly ground answers in the underlying gr

applicationsarxiv-cs-ai

Deep Learning Super Resolution for Satellite Cloud Mask Downscaling

arXiv:2608.24715v1 Announce Type: cross Abstract: A vast amount of optical satellite data is being transmitted to Earth-based servers every day, and more than half of this data is affected by haze or

researcharxiv-cs-ai

Diverse by Reasoning: Harnessing the Wisdom of LLM Crowds for Future Prediction

arXiv:2608.24001v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for future prediction, motivating the use of multiple models as a wisdom-of-the-crowd mechanism. Howe

researcharxiv-cs-ai

Don't Just Listen, Try Planning: Graph-based Retrieval-Generation Agent for Long-form Audio Meeting Understanding

arXiv:2608.24048v1 Announce Type: cross Abstract: While long-form audio meeting understanding (LAMU) is garnering growing attention, task-specific question answering (QA) datasets remain scarce. Exist

agentsarxiv-cs-ai

Enhancing Bayesian Optimization and Active Learning Through Kernel Diversity

arXiv:2608.24721v1 Announce Type: cross Abstract: Hyperparameter selection remains a key challenge in Bayesian optimization (BO) and Bayesian active learning (AL), as model misspecification can lead t

applicationsarxiv-cs-ai

Local Ai

exttt{findr}: Transparent and Fair Credit Risk Decisions through Semi-Structured Regressions

arXiv:2608.24582v1 Announce Type: cross Abstract: Credit risk models increasingly need to combine predictive accuracy with transparent explanations and auditable fairness constraints. Logistic regress

local-aiarxiv-cs-ai

Fidelity Preference, Not Demographic Preference: A Pixel-Level Attribute-Sensitivity Audit of Image Aesthetic/Preference Scorers

arXiv:2608.23593v1 Announce Type: cross Abstract: Text-to-image systems use learned aesthetic scorers to filter training data and guide generation, but whether these scores encode demographic attribut

From Dialogue to Execution: Mixture-of-Agents Assisted Interactive Planning for Behavior Tree-Based Long-Horizon Robot Execution

arXiv:2603.01113v2 Announce Type: replace Abstract: Interactive task planning with large language models (LLMs) lets robots generate high-level action plans from natural language, but over long horizo

safetyarxiv-cs-ro

Generating Biomedical Fact-Checking Reports with RL-Enhanced Agentic Search

arXiv:2608.23811v1 Announce Type: new Abstract: Automated fact-checking is essential for ensuring the reliability of public health information, yet the biomedical domain poses unique challenges. Valid

safetyarxiv-cs-ai