Search: “framework”

Toward Self-Adaptive Physical AI: Can LLM Agents Manage Long-Horizon Physical Tasks?

arXiv:2609.13436v1 Announce Type: new Abstract: Large Language Model (LLM) agents offer a promising path toward autonomously managing long-term physical tasks without human intervention. However, phys

agentsarxiv-cs-ai

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Tutorials

Towards Foundation Models for 3D Scene Understanding: Instance-Aware Self-Supervised Learning for Point Clouds

DGX agent

arXiv:2603.25165v3 Announce Type: replace Abstract: Recent advances in self-supervised learning (SSL) for point clouds have substantially improved 3D scene understanding without human annotations. Exi

tutorialsarxiv-cs-cv

15 Sept 2026

Hardware

Towards Practical Precision Agriculture: Real-Time Fruit Detection and Video Analytics on Embedded Edge Hardware

arXiv:2609.13551v1 Announce Type: new Abstract: Static-image benchmarks do not capture the computational and temporal requirements of practical orchard video analytics. This study presents an end-to-e

hardwarearxiv-cs-cv

Transfer Learning for Socioeconomic Estimation in Forced-Displacement Settings

arXiv:2609.15773v1 Announce Type: cross Abstract: Progress in inclusive household surveys has strengthened socioeconomic evidence for forcibly displaced populations, providing indispensable benchmarks

Translating the Translator: Decomposing the Cost of English-Forced Inter-Agent Communication

arXiv:2609.15079v1 Announce Type: cross Abstract: Multi-agent LLM architectures, such as LangChain and AutoGen, largely assume English as the lingua franca for internal inter-agent communication, even

agentsarxiv-cs-ai

Two-Stage Personalized Gait Phase Estimation in Stroke Survivors During Exoskeleton-Assisted Walking: An Offline Feasibility Study

arXiv:2609.14984v1 Announce Type: new Abstract: This study evaluated personalized gait phase estimation for stroke survivors using functional inertial measurement unit (IMU) alignment and two-stage se

safetyarxiv-cs-ro

TyPatch: Transforming Patches into Typestate Rules for Kernel Bug Detection

arXiv:2609.13728v1 Announce Type: cross Abstract: Historical Linux kernel patches capture defect knowledge that applies beyond their original repair sites. Recent work has shown that large language mo

Uncertainty-Guided Sparse Refinement for Action Chunking Transformer Policies

model-releasesarxiv-cs-ro

arXiv:2609.15840v1 Announce Type: new Abstract: Learning chunk-based visuomotor policies for long-horizon robot manipulation remains challenging. Recent action-chunking methods have shown promising pe

Tutorials

Understanding User Preferences of a Slope-Aware Variable-Admittance Filter for a Robot Guide Dog

arXiv:2609.15362v1 Announce Type: new Abstract: This letter investigates how the parameters of a slope-aware variable-admittance filter influence user preferences in force-based interaction with a rob

tutorialsarxiv-cs-ro

Unfair Utilities and First Steps Towards Improving Them

arXiv:2306.00636v3 Announce Type: replace-cross Abstract: Many fairness criteria constrain the policy or choice of predictors, which can have unwanted consequences, in particular, when optimizing the

safetyarxiv-cs-lg

UniCAR-RL: Seeing Better before Thinking Deeper in Visual Mathematics

arXiv:2609.13849v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) often struggle with complex mathematical visual reasoning primarily due to a lack of fine-grained perception, c

safetyarxiv-cs-ai

Unraveling the iterative CHAD

arXiv:2505.15002v3 Announce Type: replace-cross Abstract: Combinatory Homomorphic Automatic Differentiation (CHAD) was originally formulated as a semantics-driven source-to-source transformation for r

Unsupervised Point Cloud Registration via Training-Time Semantic Guidance

model-releasesarxiv-cs-cv

arXiv:2609.15228v1 Announce Type: new Abstract: Unsupervised registration of large-scale LiDAR point clouds remains challenging due to the geometric ambiguity inherent in outdoor scenes, which degrade

Utility-Guided Agent Orchestration for Efficient LLM Tool Use

arXiv:2603.19896v2 Announce Type: replace Abstract: Tool-using large language model (LLM) agents often face a fundamental tension between answer quality and execution cost. Fixed workflows are stable

safetyarxiv-cs-ai

Variational Template Matching with Statistical Fusion for Anomaly Detection in Patterned Structures

arXiv:2609.13298v1 Announce Type: cross Abstract: Anomaly detection in structured images is challenging in small-data settings where deep learning approaches are costly or impractical. Classical templ

Hardware

VC-Attention: Value Smoothing and Softmax Casting for Low-bit Attention

arXiv:2609.15810v1 Announce Type: new Abstract: Diffusion Transformers deliver state-of-the-art video generation, but their long spatiotemporal sequences make attention the dominant deployment cost, a

hardwarearxiv-cs-cv

VectorHarness: Recovering Editable, Relation-Preserving Structure from Scientific Graphics

arXiv:2609.13294v1 Announce Type: new Abstract: Converting scientific graphics into editable representations remains a challenging problem for image-to-code generation because of their heterogeneous e

agentsarxiv-cs-cv

VeriDx: Earning the Right to Diagnose with Disease-Centric Verification

arXiv:2609.14018v1 Announce Type: new Abstract: A correct diagnosis can still be reached for the wrong reasons. In clinical reasoning, every disease hypothesis creates obligations: key evidence must b

Verifiable by Construction: Claim-Level Evaluation of Verbatim Citation in Clinical Question Answering

model-releasesarxiv-cs-cl

arXiv:2609.15964v1 Announce Type: new Abstract: Large language models (LLMs) have been widely adopted for clinical question answering (QA). Current systems can attach citations to their answers, but t

VGFM: Expressive Robot Policies via Dense Value Guidance in Flow Matching

arXiv:2609.14261v1 Announce Type: cross Abstract: Recent robot learning paradigms increasingly rely on large offline datasets of robotic interactions to train control policies. Expressive generative m

safetyarxiv-cs-lg

Applications

Vision-Force Admittance Learning for Peg Insertion into a Movable Hole

arXiv:2609.14133v1 Announce Type: new Abstract: Precise manipulation in dynamic environments, whether induced by a mobile robot base or a target with unknown motion, remains a major challenge in robot

applicationsarxiv-cs-ro

WaVeFuse: Regime-Adaptive Equity Index Forecasting via Channel-Wise Wavelet Denoising and Vertical Attention Fusion

arXiv:2609.14733v1 Announce Type: new Abstract: Hybrid Deep Learning for equity index forecasting is limited by three problems: propagation of OHLCV noise into derived technical indicators (TIs), chan

Applications

WaveHiTS: Wavelet-Enhanced Hierarchical Time Series Modeling for Wind Direction Nowcasting in Eastern Inner Mongolia

arXiv:2504.06532v2 Announce Type: replace-cross Abstract: Wind direction forecasting plays a crucial role in optimizing wind energy production, but faces significant challenges due to the circular nat

applicationsarxiv-cs-ai

What Does an LLM Learn from Reinforcement Learning? A Mechanistic Interpretability Perspective with Fixed-SAE Track

arXiv:2609.15064v1 Announce Type: new Abstract: Reinforcement learning (RL) is widely utilized in large language model training to improve targeted capabilities, yet how RL reshapes a model remains po

When Correlations Mislead: Confounder-Aware Multi-View Urban Region Representation Learning

arXiv:2609.15305v1 Announce Type: cross Abstract: Urban region representation learning commonly combines heterogeneous data sources, such as mobility flows, points of interest, and land-use informatio

safetyarxiv-cs-ai

When does a scaling result justify a different allocation? A critical review of resource-allocation evidence for AI systems

model-releasesarxiv-cs-ai

arXiv:2609.14500v1 Announce Type: new Abstract: AI scaling studies increasingly evaluate systems that combine a pretrained model with retrieval, search, verification, tools, and interaction. Yet a hig

When Malicious Instructions Persist: Persistent Memory Poisoning Attack on Harness-Based Agents

model-releasesarxiv-cs-ai

arXiv:2609.13889v1 Announce Type: cross Abstract: Harness design has transformed the development of LLM-based agents by integrating memory, tool use, and runtime control. However, this design also int

When the Wrong Key Wins: Understanding and Detecting Hallucinations in LLMs

arXiv:2609.15106v1 Announce Type: new Abstract: Large language models can hallucinate even when the knowledge required for a correct answer is already available. We study this failure through a latent

researcharxiv-cs-cl

Local Ai

Where to Look and What to Use: Retrieve-Localize-Generate for Long-Term Conversational Memory Question Answering

arXiv:2609.07093v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) enables large language models (LLMs) to answer questions by accessing external knowledge and has been widely ad

local-aiarxiv-cs-cl

Who Benchmarks the Benchmarks? Towards Comprehensive Evaluation of Commonsense Reasoning Benchmarks

model-releasesarxiv-cs-cl

arXiv:2504.07825v2 Announce Type: replace Abstract: Commonsense reasoning is a key language model capability, as it is purportedly a prerequisite for many basic tasks, unlike specific factual knowledg

Local Ai

WLA^3: World Latent Action Modeling for Semantics, Dynamics, and Kinematics

arXiv:2609.15870v1 Announce Type: new Abstract: Scaling generalist policy models with heterogeneous data is limited by the lack of unified, low-noise action supervision. Human egocentric videos are ab

local-aiarxiv-cs-ro

Hardware

woma: a real-time foundation model and its fine-tuned models for endoscopy

arXiv:2609.15130v1 Announce Type: cross Abstract: woma is a real-time foundation model for gastrointestinal endoscopy: a network trained without labels on about a million endoscopy frames, from which

hardwarearxiv-cs-cv

X-WBC: A Cross-Embodiment Foundation Model for Humanoid Whole-Body Control

arXiv:2609.15213v1 Announce Type: new Abstract: Scaling humanoid whole-body control toward general-purpose deployment requires large human motion corpora and training experience shared across robot bo

safetyarxiv-cs-ro

ZAPS: Zero-Cost Active Proxy Search for Neural Architecture Search

arXiv:2609.14184v1 Announce Type: new Abstract: Neural Architecture Search (NAS) automates network design, but evaluating a single candidate requires training it to convergence, making exhaustive sear

researcharxiv-cs-lg

Local Ai

Zero-Shot Cross-Material Ptychographic Phase Reconstruction Using Deep Learning

arXiv:2609.13969v1 Announce Type: new Abstract: Ptychographic phase reconstruction is commonly formulated as an iterative inverse problem, requiring repeated object-probe updates and resulting in subs

local-aiarxiv-cs-cv

3D CT-to-PET Translation via Latent Brownian Bridge Diffusion

arXiv:2609.12860v1 Announce Type: new Abstract: Computed tomography (CT) and positron emission tomography (PET) provide complementary anatomical and functional information for cancer diagnosis and tre

safetyarxiv-cs-cv

An Empirical Markov Chain Car-Following (MC-CF) Model

arXiv:2603.27909v2 Announce Type: replace-cross Abstract: Car-following behavior is fundamental to traffic flow theory, yet traditional models often fail to capture the stochasticity of naturalistic d

AnyView: Synthesizing Any Novel View in Dynamic Scenes

model-releasesarxiv-cs-cv

arXiv:2601.16982v2 Announce Type: replace Abstract: Modern generative video models excel at producing convincing, high-quality outputs, but struggle to maintain multi-view and spatiotemporal consisten

Autonomous Precision Milling of Biological Structures via Generic Anatomical Priors and Active Boundary Perception

arXiv:2609.12530v1 Announce Type: new Abstract: Autonomous precision milling of biological structures is challenged by incomplete knowledge of target geometry, local material thickness, and critical i

agentsarxiv-cs-ro

Balancing Emotional Alignment and Semantic Consistency in Image Generation via Reinforcement Learning with Valence-Arousal Anchoring

arXiv:2609.12830v1 Announce Type: new Abstract: Continuous emotion control in text-to-image generation requires a model to improve affective alignment without changing the objects, layout, or scene de

safetyarxiv-cs-cv

Behavior Quotient Learning for Low-Rank Adaptation of LLM Agents

arXiv:2609.12896v1 Announce Type: new Abstract: LLM-based agents rely on heterogeneous interaction capabilities to accomplish complex tasks. Existing approaches often distribute these capabilities acr

Beyond ID Embeddings: Process-Grounded Language Modeling for Cognitive Diagnosis

arXiv:2609.12403v1 Announce Type: cross Abstract: Cognitive Diagnosis Models (CDMs) play a pivotal role in personalized online learning. Traditional CDMs rely on discrete, ID-based embeddings to repre

researcharxiv-cs-cl

Bias-Corrected Data Synthesis for Imbalanced Learning

arXiv:2510.26046v3 Announce Type: replace-cross Abstract: Class imbalance complicates probabilistic classification because standard training objectives emphasize majority-class performance. Synthetic

safetyarxiv-cs-lg

Applications

Breaking the Vision-Action Shortcut: Latent Interface Training for Generalizable Robotics Foundation Models

arXiv:2609.12641v1 Announce Type: new Abstract: Robot foundation models achieve strong in-distribution performance but often degrade under visual distribution shifts. When learning to generate actions

applicationsarxiv-cs-ro

Bridging Vision Foundation Model Priors with CLIP for Spatial-aware Few-shot Anomaly Detection in Medical Images

model-releasesarxiv-cs-cv

arXiv:2609.12454v1 Announce Type: new Abstract: Vision-Language Models such as CLIP enable effective few-shot medical anomaly detection (AD) via strong image-text semantic alignment. However, their gl

CanvasAnneal: Curriculum Reinforcement Learning for Diffusion Language Models

arXiv:2609.13060v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) offer promising parallel generation capabilities but lag behind autoregressive models in complex reasoning and tool-use

agentsarxiv-cs-lg

Clustering-Based Balanced Sampling and Allocation with Data Parallelism for High-Performance Fine-Tuning

arXiv:2609.12584v1 Announce Type: new Abstract: Instruction-tuning datasets for large language models (LLMs) are often large, redundant, and imbalanced, limiting efficient adaptation. Naive large-batc

researcharxiv-cs-lg

Tutorials

Cognition on Graph: Navigating Massive Knowledge Space via Cognitive Cycles and Bidirectional Graph-Text Synergy

arXiv:2609.12791v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has empowered Large Language Models (LLMs) to tackle knowledge-intensive tasks. However, navigating global, heterog

tutorialsarxiv-cs-cl