Search: “framework”

VERA: Verifiable Feasibility Representations with Counterfactual Credit for Constrained Multi-Agent Control

arXiv:2609.38889v1 Announce Type: new Abstract: Constrained multi-agent control requires more than predicting rewarding actions: an action can cease to be executable as contact windows, shared capacit

safetyarxiv-cs-lg

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VidHarness: Evolving Agent Harnesses for Cost-Efficient Long Video Understanding

DGX agent

arXiv:2609.38413v1 Announce Type: new Abstract: Vision-language models (VLMs) can answer questions about hour-long videos, but processing every frame is prohibitively expensive, even though the eviden

agentsarxiv-cs-cv

1 Oct 2026

VOSSA: Voiceprint Optimization for Streaming Speech Architectures

arXiv:2609.38887v1 Announce Type: cross Abstract: Real-time voice conversion (VC) systems commonly rely on pretrained speaker embeddings from automatic speaker verification (ASV) models. While effecti

researcharxiv-cs-cl

Local Ai

VR-JEPA: Learning Contrastive-State Latent Guidance for Generation-based Video Reasoning

arXiv:2609.40129v1 Announce Type: new Abstract: Reasoning through video generation offers a promising path toward visual intelligence by modeling latent visual states and their dynamics. However, curr

local-aiarxiv-cs-cv

What Was Said, Not What Was 'Thought': Type-6 Logic for CoT Verification

arXiv:2609.38420v1 Announce Type: cross Abstract: We introduce Type-6 logic, a variant of dynamic epistemic logic augmented with two operators (uncertainty and recurrence), designed to model the infer

When Integral Meets Decomposition: A Signal-Level Self-Supervised Feature Decompose Paradigm for Multi-Modal Image Fusion

arXiv:2609.39004v1 Announce Type: new Abstract: Multimodal image fusion (MMIF) aims to integrate complementary information from different modalities into a high-quality fused image and support downstr

WinoTS: Wavelet-based Self-Distillation for Time Series Models

arXiv:2609.39337v1 Announce Type: cross Abstract: Self-supervised pre-training of time series models is currently dominated by next-token prediction and reconstruction objectives. In continuous-valued

WorkGenesis: Building the Worlds That Teach Agents to Work

arXiv:2609.39325v1 Announce Type: new Abstract: The ability of Large Language Model (LLM) agents to complete daily and professional work is receiving increasing attention. Training such agents require

A theoretical model of dynamical grammatical gender shifting based on set-valued set function

arXiv:2603.03510v3 Announce Type: replace-cross Abstract: This study investigates the diverse characteristics of nouns, focusing on both semantic (e.g., countable/uncountable) and morphosyntactic (e.g

Achieving detailed medial temporal lobe segmentation with upsampled isotropic training from implicit neural representation

arXiv:2508.17171v3 Announce Type: replace Abstract: Imaging biomarkers in magnetic resonance imaging (MRI) are important tools for diagnosing, tracking and treating Alzheimer's disease (AD). Neurofibr

Act First, Reason Later: Accelerating On-Policy Distillation for Multi-Turn Agents via Reference-Conditioned Inverse Dynamics

model-releasesarxiv-cs-cl

arXiv:2609.36608v1 Announce Type: cross Abstract: On-policy distillation (OPD) trains multi-turn language agents with dense teacher supervision on student-generated responses. However, standard think-

Agents

ActiveSAM: Fast and Accurate Open-Vocabulary Semantic Segmentation with Frozen SAM 3

arXiv:2606.16996v2 Announce Type: replace-cross Abstract: Segment Anything Model 3 (SAM 3) provides a strong frozen backbone for concept-prompted segmentation, but applying it directly to open-vocabul

agentsarxiv-cs-ai

actr: aligning thoughts and responses for multilingual safety in reasoning llms

arXiv:2609.37054v1 Announce Type: new Abstract: Ensuring the safety of reasoning large language models (LLMs) across languages is essential for their reliable deployment. However, when exposed to jail

AdaKerNet: Neural Kernel Decoding for Task-Adaptive Prediction with Multimodal Large Models

arXiv:2609.36368v1 Announce Type: cross Abstract: Large foundation models have been introduced with the promise of efficient adaptation to downstream tasks. Yet, under limited supervision, MLLMs, an i

Applications

AdaST: Adaptive Coupling for Spatial-Temporal Forecasting

arXiv:2609.36119v1 Announce Type: new Abstract: Spatial-temporal (ST) forecasting underpins many real-world systems such as traffic, climate, and energy networks. While existing methods implicitly ass

applicationsarxiv-cs-ai

AerialDojo-200K: A Large-Scale Benchmark Suite for Open-World Aerial Object-Goal Search

arXiv:2609.36066v1 Announce Type: cross Abstract: Open-world aerial object-goal search is a foundational yet challenging task, requiring aerial agents to autonomously explore large-scale, unstructured

Tutorials

AESOP: Asymmetric Human-Camera Generation with Translation-Intensity Control

arXiv:2609.37229v1 Announce Type: new Abstract: Human motion defines an action, while a camera trajectory determines how it is presented. Camera generation for a given human motion and joint human-cam

tutorialsarxiv-cs-cv

AESplat: Advancing Pose-Free Feed-Forward 3D Gaussian Splatting via Decoupled Appearance Modeling

arXiv:2609.36693v1 Announce Type: new Abstract: Pose-free feed-forward 3D Gaussian Splatting (3DGS) has demonstrated remarkable potential for generalized novel view synthesis. However, existing method

AffectReveal: Event-Grounded Emotion Recognition Beyond Visual Appearances

arXiv:2609.36563v1 Announce Type: new Abstract: Visual emotion recognition commonly assumes that all evidence required for prediction is contained in the observed image or video. Yet the same visible

AMU:Admission and Memory Update for Personalized Conversations---Structured Memory with SLM Guided Control

arXiv:2609.36976v1 Announce Type: new Abstract: Large language models (LLMs) have become the foundation of personalized assistants, but maintaining persistent user memory across long-term interactions

researcharxiv-cs-cl

An Efficient Machine Learning Approach for Degradation Forecasting in AEM Water Electrolysis

arXiv:2609.37941v1 Announce Type: new Abstract: This study provides a data-driven analysis of a novel dataset of single-cell Anion Exchange Membrane water electrolyzers (AEMWE), operated under constan

researcharxiv-cs-lg

Anatomy-Aware Prediction of Bronchoscopic Accessibility from 3D CT

model-releasesarxiv-cs-cv

arXiv:2609.37386v1 Announce Type: new Abstract: Pre-operative planning for bronchoscopy is critical for the diagnosis of lung lesions. Current accessibility assessment relies on subjective manual insp

Agents

Asymmetric Scout-Worker Reconnaissance for Route Validation in Unknown Environments

arXiv:2609.36537v1 Announce Type: new Abstract: This paper studies asymmetric scout-worker reconnaissance in unknown environments, where a small, agile autonomous scout explores routes for a larger wo

agentsarxiv-cs-ro

Local Ai

AutoLoCo: Communication Efficient Distributed LLM Training via Adaptive Synchronization

arXiv:2609.36662v1 Announce Type: cross Abstract: The pre-training of Large Language Models (LLMs) is increasingly conducted across multiple data centers. As training scales to a larger number of acce

local-aiarxiv-cs-ai

Automated Evaluation of Multi-Turn Dialogues in In-Car Conversational Assistants

arXiv:2609.35812v1 Announce Type: new Abstract: In-car conversational assistants (ICAs) are increasingly integrated into vehicles to support route planning, vehicle control, and information access. En

safetyarxiv-cs-cl

BaLEEN: Biasing with Latent Encoded Entities for Context-Aware ASR

arXiv:2609.36913v1 Announce Type: cross Abstract: Transcribing domain-specific entities and rare proper nouns remains a major challenge in automatic speech recognition (ASR). In this paper, we propose

Bathtubs, Boundaries, and Sandboxes: AI Regulatory Learning under Legal Uncertainty

arXiv:2601.04094v4 Announce Type: cross Abstract: Effective regulation of AI is a defining policy challenge, driven by their integration into all aspects of society. To remain responsive to their rapi

BCNav: Bearing-Conditioned Depth Policies for Sound Source Navigation

arXiv:2609.37084v1 Announce Type: new Abstract: The ability to navigate toward sound sources extends a robot's reach beyond its visual field, enabling response to auditory events in unknown environmen

safetyarxiv-cs-ro

Beam Search as Test-Time Self-Distillation via Counterfactual Contexts

arXiv:2609.37041v1 Announce Type: cross Abstract: Self-Distillation Fine-Tuning (SDFT) enables a language model to act as its own teacher: by conditioning on a demonstration, the model produces an imp

BeatDance: Generating Beat-Consistent 3D Dance with Hierarchical Spatial-Temporal Modeling

model-releasesarxiv-cs-cv

arXiv:2609.37400v1 Announce Type: new Abstract: Generating realistic 3D dance from music is a challenging task that requires accurate synchronization with musical rhythms while capturing the spatial c

Better Nearest Neighbor Graph Indices via (Efficient) LLM-Guided Pruning

arXiv:2609.36359v1 Announce Type: new Abstract: Graph-based approximate nearest neighbor search (ANNS) is widely used for large-scale semantic search. Its indices are constructed primarily based on ge

Beyond Attention Imbalance: Mitigating Hallucinations via Spectral Surgery

arXiv:2609.37263v1 Announce Type: new Abstract: While Large Vision-Language Models (LVLMs) achieve remarkable success, hallucinations remain a significant barrier to their reliable deployment. Recent

Applications

Beyond Conditional Independence: Root Cause Analysis with Deep Causal Models

arXiv:2609.36771v1 Announce Type: cross Abstract: Root cause analysis (RCA) is a critical problem in many real-world scenarios. RCA enables the identification of faulty or failing mechanisms in a syst

applicationsarxiv-cs-ai

BrainNet Studio: A Unified Toolkit for Brain Network Construction, Intelligent Analysis, and Visualization

arXiv:2609.37956v1 Announce Type: new Abstract: Brain networks characterize structural and functional relationships among brain regions and support research on cognition, brain disorders, and brain-co

Breaking the Illusion of Review Reliability under Static Evaluation: SCOPE Fuzzing for LLM-based Scientific Reviewers

arXiv:2609.37097v1 Announce Type: new Abstract: The rapid growth of submissions and reviewing workload has accelerated the use of large language models (LLMs) in peer review. Prior studies suggest tha

Calibrate the Decisions That Change the Future: On-Policy Post-Training Quantization for Multimodal Large Language Models

arXiv:2609.36828v1 Announce Type: new Abstract: Post-training quantization (PTQ) lowers deployment cost for multimodal large language models, but calibration typically reconstructs fixed sequences wit

Calibration-First Cross-Cohort Multimodal Temporal Learning for Transferable Asthma-Risk Forecasting

arXiv:2609.35795v1 Announce Type: cross Abstract: Asthma deterioration forecasting must remain reli- able when patient populations, sensor ecosystems, and available modalities change across cohorts. E

Causal-EVC: Breaking Emotional Spurious Causality via Spatiotemporal Grounding and Counterfactual Intervention

model-releasesarxiv-cs-cv

arXiv:2609.36776v1 Announce Type: new Abstract: Emotional Video Captioning aims to generate factually accurate and emotionally empathetic descriptions. While recent methods have recognized the importa

CF-LoRA: Decoupled Factor Aggregation and Adaptation-Aware Client Clustering for Federated LoRA Fine-Tuning

arXiv:2609.36986v1 Announce Type: new Abstract: Federated LoRA fine-tuning enables parameter-efficient adaptation of pre-trained models without sharing private data, but suffers from two fundamental m

ChronoSRL: Temporal Geometry for Self-Supervised Reinforcement Learning

arXiv:2609.36238v1 Announce Type: new Abstract: A goal that is close in space can be far away in time. Obstacles, terrain, and the agent's own capabilities determine how long it takes to get there. Ye

Tutorials

Co-PiLOT: Constrained Physics-Informed Latent Optimization for Target-Driven Inverse Design

arXiv:2609.37875v1 Announce Type: new Abstract: Inverse design of physical systems (molecules, devices, microstructures) often reduces to optimizing a high-dimensional structure against an expensive b

tutorialsarxiv-cs-ai

Agents

CoDimRecon: Agentic Reconstruction of Sim-Ready 3D Scenes with Deformable Curves, Surfaces, and Volumes

arXiv:2609.36024v1 Announce Type: new Abstract: Reconstructing simulation-ready 3D scenes from real-world observations enables robotics, gaming, and immersive applications, yet existing methods largel

agentsarxiv-cs-cv

Local Ai

Collision-Aware and Observation-Aligned Object-Centric Scene Reconstruction from Point Cloud

arXiv:2609.37260v1 Announce Type: new Abstract: Object-centric scene reconstruction requires completing partial object observations while preserving metric alignment and avoiding collisions with the s

local-aiarxiv-cs-cv

COMiT: Learning Structured Visual Tokens through Sequential Communication

arXiv:2602.20731v2 Announce Type: replace-cross Abstract: Discrete image tokenizers provide a sequential interface for vision and multimodal models, but are typically optimized for reconstruction or c

Complexity-Aware Evaluation of LLM Comprehension

arXiv:2609.37405v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for software engineering tasks that require understanding existing source code, including behavior

Contact-Adaptive Robotic Ultrasound Probe Control for Tissue Exploration and Continuous Task-Relevant Visualization Using Robot-Free Image-Motion Demonstration

arXiv:2609.37456v1 Announce Type: new Abstract: Robotic ultrasound commonly targets standardized views, predefined scanning protocols, or expert-scan reproduction. We target a different role: while a

safetyarxiv-cs-ro

Controlled Decoding Attacks on Black-Box LLMs

arXiv:2609.36956v1 Announce Type: cross Abstract: Manipulating next-token probabilities during generation can bypass the safety alignment of large language models. Existing approaches, however, rely o

CoRe: Co-Evolving Reward Models for Mitigating Latent Reward Hacking in Video Diffusion Models

arXiv:2609.36245v1 Announce Type: new Abstract: Latent reward models (LRMs) enable efficient alignment of video diffusion models by scoring intermediate states directly in latent space. However, we fi