Search: “papers”

arXiv:2609.00706v1 Announce Type: new Abstract: The SAIR Mathematics Distillation Challenge on Equational Theories asks a solver to classify whether one magma identity implies another and, for either

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A Lagrangian View of Flow Matching

DGX agent

arXiv:2609.00198v1 Announce Type: new Abstract: Modern explicit-time generative models, such as Flow Matching [Lipman et al., 2023] and Rectified Flow [Liu et al., 2023], are typically derived top-dow

researcharxiv-cs-cv

2 Sept 2026

A Sensor-Adaptive Incremental Learning Framework for Artifact Detection in Satellite Precipitation Data

arXiv:2609.01514v1 Announce Type: cross Abstract: Historically, retrieving rainfall data from satellite imagery has been the domain of space agencies. However, in recent years, the development of chea

Applications

Adaptive Critical Token-Aware Retrieval for Repository-Level Code Generation

arXiv:2609.01601v1 Announce Type: cross Abstract: The repository-level code generation task requires synthesizing code that satisfies task requirements while remaining consistent with the target repos

applicationsarxiv-cs-ai

Adaptive Depth-Map-Guided Bundle Adjustment for Correspondence-Free Multi-View Point Cloud Registration

arXiv:2609.01089v1 Announce Type: new Abstract: Robotic processing of irregular steel scrap requires dense 3-D measurement to replace manual visual assessment in hazardous cutting workcells. The recon

researcharxiv-cs-ro

AgentFactory: Towards Automated Agentic System Design and Optimization

arXiv:2609.01045v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities as powerful components in agentic systems, enabling sophisticated reasoning and c

agentsarxiv-cs-ai

Local Ai

An Intelligent Decision Support System for Emotion Monitoring using Microscopic Fixational Dynamics

arXiv:2609.00846v1 Announce Type: new Abstract: The rising prevalence of psychological disorders necessitates effective emotion monitoring, yet current methods relying on facial or physiological signa

local-aiarxiv-cs-cv

Artificial Rosetta Stone: Constrained Maximum A Posteriori (MAP) Reconstruction of Symbolic Raga Sequences via Order-k Markov Models

arXiv:2609.01064v1 Announce Type: cross Abstract: Reconstructing a damaged musical fragment is an inverse problem: the observed sequence contains partial information, while a raga encodes constraints

Athena: Vulnerability-Affected Library Identification via Knowledge Graph Completion

arXiv:2609.01187v1 Announce Type: cross Abstract: A single vulnerability in a widely used library can cascade through millions of dependent applications, yet more than half of vulnerability database e

Attention Sensitivity Is Not Enough: Dissociating Attention-Level and Behavioural In-Context Learning under Fine-Tuning

model-releasesarxiv-cs-ai

arXiv:2609.00064v1 Announce Type: cross Abstract: In-context learning (ICL) lets large language models adapt to new tasks from demonstrations, and fine-tuning can erode this behaviour. Many preservati

AutoXRD: Autonomous LLM Agents and Comprehensive Evaluation for Powder Diffraction Analysis

model-releasesarxiv-cs-ai

arXiv:2609.00070v1 Announce Type: cross Abstract: Powder X-ray diffraction (XRD) is central to materials characterization, yet reliable end-to-end automation remains challenging. An XRD agent must int

Local Ai

Behavior--Realization Separation for Constrained Physical Human--Robot Interaction

arXiv:2609.00669v1 Announce Type: new Abstract: Physical human--robot interaction software often couples desired-behavior specification with constrained realization; we treat these as separate layers.

local-aiarxiv-cs-ro

Benchmarking Spatial, Spectral, and Self-Supervised Cues for Face Forgery Detection under Realistic Degradation

model-releasesarxiv-cs-cv

arXiv:2609.01511v1 Announce Type: new Abstract: Face forgery detectors often achieve strong results on controlled benchmarks, but their reliability under realistic image degradations remains limited.

Beyond Token Positions: Safety Alignment Across Denoising Steps in Diffusion Language Models

arXiv:2609.00495v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text through iterative denoising rather than left-to-right decoding. This generation paradigm introdu

safetyarxiv-cs-ai

Breaking the Structural Identity: Personalized Federated LoRA Fine-tuning under Rank Heterogeneity

arXiv:2609.00632v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable success across diverse domains, but their adaptation to privacy-sensitive, distributed datasets

Applications

CADKnitter: Compositional CAD Generation from Text and Geometry Guidance

arXiv:2512.11199v2 Announce Type: replace Abstract: Computer-aided design (CAD) defines 3D models as compact, precise, and editable representations, making it directly useful for several fields. Recen

applicationsarxiv-cs-cv

Can Large Language Models Forecast What Researchers Study Next?

model-releasesarxiv-cs-cl

arXiv:2609.00747v1 Announce Type: new Abstract: Large language models increasingly generate research ideas, yet judging their novelty or feasibility at generation time does not establish whether they

CoMMET: A Psychologically Grounded Benchmark for Evaluating Theory of Mind in Multimodal LLMs

model-releasesarxiv-cs-cl

arXiv:2603.11915v2 Announce Type: replace Abstract: Theory of Mind (ToM)-the ability to reason about the mental states of oneself and others-is a cornerstone of human social intelligence. As Multimoda

Context-Aware Intelligent Vehicles

arXiv:2609.00682v1 Announce Type: new Abstract: Intelligent vehicles increasingly support adaptive applications beyond driving themselves, ranging from context-aware ADAS and automated driving to in-c

safetyarxiv-cs-ro

Convergence issues in Relational Concept Analysis based on AOC-posets

arXiv:2609.00054v1 Announce Type: new Abstract: Formal Concept Analysis (FCA) is an approach for conceptual classification building and rule discovery from a binary table describing a set of objects b

researcharxiv-cs-lg

Conversation Coach: A Voice-enabled AI System that Helps Practice Difficult Workplace Conversations

arXiv:2609.00441v1 Announce Type: new Abstract: Effective manager-employee communication is critical for retaining high performers and developing underperformers, yet training managers in these skills

safetyarxiv-cs-ai

Counterfactual Closing-Acceleration Risk: An Anticipatory Surrogate Safety Measure for the Blind Region of Car-Following

model-releasesarxiv-cs-ro

arXiv:2609.00370v1 Announce Type: cross Abstract: Surrogate safety measures allow road-safety assessment from trajectory data in which crashes are absent, yet the dominant proximity measures - time-to

Ctrl-F-Resist. Practices, Challenges, and Technical Needs of Civil Society Organizations Monitoring the Far-Right Online

arXiv:2609.00808v1 Announce Type: cross Abstract: As far-right actors increasingly exploit online platforms to disseminate ideology and mobilize supporters, civil society organizations (CSOs) play a v

safetyarxiv-cs-ai

Hardware

CUDA-Harness: Harnessing Agentic CUDA Kernel Generation and Optimization from Natural Language

arXiv:2609.00058v1 Announce Type: cross Abstract: Developing high-performance CUDA kernels demands specialized knowledge in algorithm implementation, correctness validation, and hardware-aware paralle

hardwarearxiv-cs-ai

Tutorials

Dense Process Supervision for Search Agents via Fact Utility Estimation

arXiv:2609.00833v1 Announce Type: new Abstract: Reinforcement learning (RL) for search agents typically relies on outcome rewards. However, it often fails to achieve effective credit assignment, due t

tutorialsarxiv-cs-cl

Design and Implementation of a Kalman Filter-Infused Algorithm for Tilt Estimation

arXiv:2609.00730v1 Announce Type: new Abstract: Accurate tilt angle estimation is important in many engineering applications, such as robotics, motion tracking, and embedded control systems. However,

Designing Proactive Thought Partners for Writing

arXiv:2609.01588v1 Announce Type: cross Abstract: Writing involves diverse cognitive activities, from ideation to revision, and writers' needs vary across individuals and moments. Proactive AI promise

Detoxifying Toxic Communication: A Design Science Approach to Responsible AI

arXiv:2609.00361v1 Announce Type: cross Abstract: Toxic language in digital workplaces such as pejoratives, sarcasm, condescension, and subtle incivility can erode trust, morale, and collaboration. Ex

safetyarxiv-cs-cl

DICE: Distilling Classifier-Free Guidance into Text Embeddings

arXiv:2502.03726v3 Announce Type: replace Abstract: Text-to-image diffusion models are capable of generating high-quality images, but suboptimal pre-trained text representations often result in these

safetyarxiv-cs-cv

Diffusion Based Unpaired Data Learning for Inverse Problems

arXiv:2609.01370v1 Announce Type: new Abstract: Data is important in many deep learning-based inverse problem solvers. However, obtaining sufficient paired data in many scenarios remains highly challe

Disciplined Bilevel Programming

arXiv:2609.00644v1 Announce Type: cross Abstract: Bilevel optimization provides a natural modeling language for hierarchical decision problems. However, applying existing numerical solvers usually req

researcharxiv-cs-lg

DNC-IMM: Early Lane-Change Intention Recognition via Neural Calibration Based on Driving Context Information

arXiv:2609.01120v1 Announce Type: cross Abstract: Early recognition of lane-change intention is essential for proactive decision-making in autonomous driving and advanced driver assistance systems. Th

agentsarxiv-cs-ai

Does Reasoning Mitigate Backdoor Attacks? A Neuro-Symbolic Perspective

arXiv:2609.00464v1 Announce Type: cross Abstract: Neuro-Symbolic (NeSy) AI has recently emerged as a novel paradigm to enable trustworthy AI, aiming at integrating sub-symbolic neural perception with

DualDiff3D: Dual Structure-Appearance Diffusion Priors for Reliability-Enhanced 3D Gaussian Splatting

arXiv:2609.01516v1 Announce Type: new Abstract: While 3D Gaussian Splatting (3DGS) has revolutionized 3D reconstruction and novel-view synthesis, scenarios with limited input views often lead to poor

DynaNDE: Dynamic Near-Data Expert Scheduling for Batched MoE Inference

arXiv:2609.00407v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models enable efficient scaling of large language model (LLM) inference but suffer from substantial data-movement overhead wh

EAAE: Energy-Aware Autonomous Exploration for UAVs in Unknown 3D Environments

arXiv:2603.15604v2 Announce Type: replace Abstract: Battery-powered multirotor unmanned aerial vehicles (UAVs) can rapidly map unknown environments, but mission performance is often limited by energy

agentsarxiv-cs-ro

Efficient and Robust Absolute Pose Estimation via Gravity-Prior-Driven Transformation Decoupling and Pose Refinement

model-releasesarxiv-cs-cv

arXiv:2609.00713v1 Announce Type: new Abstract: Estimation of the absolute pose of an object is an essential task for various robotic applications. Recently, incorporating gravity direction as prior i

Endoscopic Depth Estimation Based on Deep Learning: A Survey

arXiv:2507.20881v3 Announce Type: replace Abstract: Endoscopic depth estimation is a critical technology for improving the safety and precision of minimally invasive surgery. It has attracted consider

safetyarxiv-cs-cv

EULER: Exploring Underused Links with Evidence-Checked Return for Multi-Agent Mathematical Discovery

arXiv:2609.00032v1 Announce Type: new Abstract: Mathematical communities work with different objects, invariants, and tools, so transferring a problem across them is expensive and often skipped. We pr

agentsarxiv-cs-ai

Exact Risk-Complexity Laws for Projective Boundaries in Scenario Optimization and Distribution-Free Certification

arXiv:2609.01355v1 Announce Type: cross Abstract: Scenario optimization, conformal prediction, and related distribution-free certification methods use finite samples to construct decisions or predicti

Exploiting Stability-Plasticity Asymmetry in Pretrained Detectors for Incremental Object Detection

model-releasesarxiv-cs-cv

arXiv:2504.10214v2 Announce Type: replace Abstract: Pretrained model-based incremental object detection (PTMIOD) leverages the rich detection priors of pretrained detectors to learn new categories inc

Tutorials

FedReview: Review and Dispose Poisoned Updates without Validation Datasets or Historic Knowledge

arXiv:2402.16934v2 Announce Type: replace-cross Abstract: Federated learning has emerged as a decentralized approach for training high-performance models without accessing user data. Despite its effec

tutorialsarxiv-cs-ai

Few-Shot Out of Domain Intent Detection with Covariance Corrected Mahalanobis Distance

arXiv:2609.00961v1 Announce Type: new Abstract: Conversational agents like chatbots and voice assistants are trained to understand and respond to user intents. On encountering an utterance with an int

FoldingAgent: Inferring Parametric Origami Procedures from Demonstration Videos

model-releasesarxiv-cs-ai

arXiv:2609.00377v1 Announce Type: cross Abstract: We present FoldingAgent, an agentic framework for inferring explicit parametric folding programs directly from origami demonstration videos. Our frame

Tutorials

Forbid Your Attention: Fooling Multimodal Large Language Models by Selectively Removing Intrinsic Focus in Spectral Domain

arXiv:2609.00788v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have extended the capability of large language models (LLMs) to process more contextual multimodal information,

tutorialsarxiv-cs-cv

From Tool Use to Technological Agency: LoopCAT as a Local-First, Open-Source Tool for Translation Technology Education

model-releasesarxiv-cs-cl

arXiv:2609.00344v1 Announce Type: new Abstract: Translation students need to learn both how to use translation technologies and how to judge the choices those technologies make available. This article

Generative artificial intelligence for reliable mechanistic reasoning for corrosion

arXiv:2609.00099v1 Announce Type: new Abstract: Corrosion accounts for approximately 4% of global GDP, and reliable prediction is essential for timely mitigation. Machine learning effectively predicts

Applications

GENIE: Watermarking Graph Neural Networks for Link Prediction

arXiv:2406.04805v4 Announce Type: replace-cross Abstract: The rapid adoption, usefulness, and resource-intensive training of Graph Neural Network (GNN) models have made them an invaluable intellectual

applicationsarxiv-cs-lg