Search: “papers”

Slot-RAE: Streamlining Object-Centric Learning via Direct Representation Auto-Encoders

arXiv:2607.11196v2 Announce Type: replace Abstract: Deploying object-centric models for real-world scene understanding typically requires complex pipelines to achieve both robust scene decomposition a

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SparSP: Exploiting Communication Sparsity for Sequence-Parallel Video DiTs

DGX agent

arXiv:2609.32197v1 Announce Type: cross Abstract: Diffusion Transformers have become the dominant architecture for video generation. Their substantial computational cost motivates scaling inference ac

hardwarearxiv-cs-lg

29 Sept 2026

Agents

SPOC-Net: Single-Primitive Online Composition Network for GNSS Jamming Set Recognition

arXiv:2609.34875v1 Announce Type: new Abstract: Reliable positioning, navigation, and timing support intelligent transportation, autonomous systems, and space-air-ground integrated networks. However,

agentsarxiv-cs-cv

Stabilizing the Dynamic Low-Rank Training

arXiv:2609.32615v1 Announce Type: new Abstract: Training neural networks directly in a low-rank parameterization is an appealing route to reducing memory, compute, and storage simultaneously during bo

Applications

STAR: Adaptive Spatial-Temporal Normalization for Unified Microservice Incident Management

arXiv:2609.31645v1 Announce Type: new Abstract: Automated incident management in large-scale microservice systems relies on learning robust representations from multimodal observability data, includin

applicationsarxiv-cs-lg

Statistical Testing for Multiple Instance Learning via Selective Inference with Applications to Computational Pathology

arXiv:2609.31712v1 Announce Type: new Abstract: Multiple instance learning (MIL) is widely used in computational pathology because it enables weakly supervised analysis of whole-slide images (WSIs) wi

Tutorials

Style-Driven Data Synthesis and Degradation-Aware Enhancement for Ultrasound Image Restoration

arXiv:2609.35120v1 Announce Type: new Abstract: Low-cost handheld ultrasound devices can be widely deployed compared to professional hospital ultrasound machines. However, their images suffer from com

tutorialsarxiv-cs-cv

Summarize Before Grounding: Query-Guided Chunk Condensation for Long-Video Temporal Grounding

arXiv:2609.34598v1 Announce Type: new Abstract: Video temporal grounding (VTG) aims to localize the video interval corresponding to a language query. Recent large vision-language models (LVLMs) show g

SWT: Self-Supervised Video Object Segmentation via Sliding, Wavelet and Transportation

model-releasesarxiv-cs-cv

arXiv:2609.31725v1 Announce Type: new Abstract: Video Object Segmentation (VOS) aims to accurately segment target objects from consecutive video frames and track the changes of the objects in each fra

Symmetric Composition of Anisotropic Operators for Global Subseasonal-to-Seasonal Climate Forecasting

arXiv:2602.15040v2 Announce Type: replace-cross Abstract: Accurate global Subseasonal-to-Seasonal (S2S) climate forecasting is critical for disaster preparedness and resource management, yet it remain

SyncEdit: Rethinking Lip Synchronization as Editing with Audio-Driven Diffusion Models

arXiv:2603.09084v2 Announce Type: replace Abstract: Lip synchronization refers to the task of modifying facial lip movements such that they are temporally aligned with a given audio signal. It is a fu

Synthetic data for ratemaking: imputation-based methods vs adversarial networks and autoencoders

arXiv:2509.02171v3 Announce Type: replace-cross Abstract: Actuarial ratemaking depends on high-quality data, yet access to such data is often limited by the cost of obtaining new data, privacy concern

Synthetic Thermal Image Generation for Real-Time Animal Detection Under Low-Visibility Conditions

arXiv:2609.32944v1 Announce Type: new Abstract: Wildlife-vehicle collisions remain a significant road safety concern, particularly during nighttime and low-visibility conditions when RGB-based percept

Hardware

Terrain-Aware Autonomous Planetary Exploration for Exteroceptive-Proprioceptive Mapping with Quadruped Scouts

arXiv:2609.35493v1 Announce Type: new Abstract: Autonomous planetary exploration requires robots to navigate unknown, uneven terrain while assessing risk, traversability, and energetic cost. Quadruped

hardwarearxiv-cs-ro

The Devil in the Details: Emergent Misalignment, Format and Coherence in Open-Weights LLMs

arXiv:2511.20104v2 Announce Type: replace Abstract: Prior work has shown that fine-tuning models on a narrow domain with misaligned data can lead to broad misalignment - a phenomenon termed 'emergent

The Price of Locality: Why Forward-Forward Underperforms Backpropagation?

arXiv:2609.33240v1 Announce Type: new Abstract: The Forward-Forward Algorithm (FFA) replaces backpropagation (BP) with layer-wise local contrastive objectives, eliminating the backward pass and the ne

The Selection Rule Decides the Winner: A Pre-Registered Audit of Open-Set Graph Anomaly Detection

arXiv:2609.33370v1 Announce Type: new Abstract: Open-set graph anomaly detection trains on a few labeled anomalies from one class and must also find anomaly classes that were never labeled. Published

THEIA: A Multimodal Dataset and Benchmark for Vision-Language Analysis of Layout

arXiv:2609.35035v1 Announce Type: new Abstract: The integration of artificial intelligence into computer-aided design frameworks has sparked a shift in the design of analog integrated circuits (ICs),

TokenCast: Forecasting Token Consumption During LLM Agent Execution

arXiv:2609.35760v1 Announce Type: new Abstract: When a large language model (LLM) agent executes the same task, token consumption can vary by over an order of magnitude across runs. The agent chooses

safetyarxiv-cs-lg

TopoMamba: A Load-Support Relation-Guided Multi-Directional State-Space Model for Topology Optimization

arXiv:2609.33688v1 Announce Type: cross Abstract: Deep learning has emerged as an efficient alternative for predicting high-performance material distributions in topology optimization. Existing method

Towards Eliminating Catastrophic Forgetting in the Curriculum Learning of Math Reasoning Tasks

arXiv:2609.33655v1 Announce Type: new Abstract: Curriculum learning has found broad application across numerous domains. Nevertheless, its effectiveness is intrinsically curtailed by catastrophic forg

Local Ai

Towards More Trustworthy and Interpretable LLMs for Code through Syntax-Grounded Explanations

arXiv:2407.08983v2 Announce Type: replace-cross Abstract: Trustworthiness and interpretability are inextricably linked concepts for LLMs. The more interpretable an LLM is, the more trustworthy it beco

local-aiarxiv-cs-lg

TRACE: Trajectory-Based Safety Patch Learning for LLM Post-Training Realignment

arXiv:2607.16242v2 Announce Type: replace Abstract: Fine-Tuning-as-a-Service (FTaaS) platforms let users perform supervised fine-tuning (SFT) on customized data, but this pipeline can erode model safe

safetyarxiv-cs-lg

Transformer MLP Gate Thresholds Are Couplings to a Carried Reference Direction

arXiv:2609.31956v1 Announce Type: cross Abstract: The corpus-mean direction of a transformer's residual stream is a component shared across all inputs, and is commonly removed by mean-centering before

Typed Decision Models: An Early Evidence Audit and Evaluation Checklist

arXiv:2609.32160v1 Announce Type: cross Abstract: Typed decision models (TDMs) return probability distributions over caller-defined options without generating text. TypeSafe released Jev, a commercial

Understanding the Subspace Stabilization of the Hessian and Gradient Covariance Matrix

arXiv:2609.31983v1 Announce Type: new Abstract: The phenomenon of the top subspace stabilization of the Hessian matrix is an surprising and critical aspect in study of the second-order information of

UniBYD: A Unified Framework for Learning Robotic Manipulation Across Embodiments Beyond Imitation of Human Demonstrations

model-releasesarxiv-cs-ro

arXiv:2512.11609v3 Announce Type: replace Abstract: In embodied intelligence, the embodiment gap between robotic and human hands brings significant challenges for learning from human demonstrations. A

Unlocking Geodesic Gromov-Wasserstein Distances for 3D Modeling

arXiv:2609.32824v1 Announce Type: new Abstract: extit{Gromov-Wasserstein Distances} (GWDs) provide quantitative ways of comparing probabilistic distributions defined on different metric spaces by appl

Verifying the Linear Representation Hypothesis: How Interpretable Are Vision SAEs?

arXiv:2609.35020v1 Announce Type: new Abstract: Vision Sparse Autoencoders (SAEs) have become a popular tool in Mechanistic Interpretability due to their presumed ability to disentangle complex featur

VIDEAS: Distilling Explicit Action Semantics from Demonstration Videos for World Models via Prior-Guided Simulation

model-releasesarxiv-cs-ro

arXiv:2609.33464v1 Announce Type: new Abstract: World models learn internal representations of environment dynamics to predict future states, enabling agents to optimize action plans without physical

What masking geometry works best for EEG foundation models?

arXiv:2609.33487v1 Announce Type: new Abstract: EEG foundation models hold promise for scalable brain-signal decoding across clinical and cognitive neuroscience applications, yet their pre-training pi

When Should Humans Step In? Optimal Human Dispatching in AI-Assisted Decisions

arXiv:2603.13688v2 Announce Type: replace-cross Abstract: AI systems increasingly assist decision making by producing cheap factor-level assessments of complex inputs, but these assessments can be bia

Word Similarity Datasets for Indian Languages: Annotation and Baseline Systems

arXiv:2609.34138v1 Announce Type: cross Abstract: With the advent of word representations, word similarity tasks are becoming increasing popular as an evaluation metric for the quality of the represen

WorldPlay2: Extending Real-Time Interactive World Models in Control and Horizon

arXiv:2609.35560v1 Announce Type: new Abstract: Interactive world models require responding in real time to versatile controls and maintaining long-horizon consistency. However, modeling heterogeneous

ZeroGAR: Benchmarking the Adversarial Robustness of Zero-Shot Graph Models

arXiv:2609.33314v1 Announce Type: new Abstract: Zero-shot graph models (ZGMs), which learn transferable knowledge from source graphs and directly apply to unseen target graphs without any adaptation,

A Benchmark Framework for Screening Automation in Systematic Reviews

model-releasesarxiv-cs-cl

arXiv:2609.30298v1 Announce Type: new Abstract: Systematic reviews (SR) are essential for evidence-based research, but their screening phase is highly time-consuming and labor-intensive. Large languag

A Synthetic Ground-Truth Framework for the Evaluation of Explainable AI Methods

arXiv:2609.30397v1 Announce Type: new Abstract: Evaluating explainable Artificial Intelligence (XAI) methods is a challenging task due to the lack of reliable evaluation procedures and, in particular,

researcharxiv-cs-ai

Tutorials

A Unified Account of Concepts and Chunks

arXiv:2609.30414v1 Announce Type: cross Abstract: Cognitive psychology has studied how people encode, use, and learn concepts that describe categories, and how they represent, recognize, and acquire c

tutorialsarxiv-cs-ai

Accuracy Evaluation of INS/ZUPT Filtering Methods Based on Different Geometric Error Definitions

arXiv:2609.31057v1 Announce Type: new Abstract: Geometric filters have recently been introduced to improve the accuracy and consistency of inertial-based integrated navigation systems. Error states we

researcharxiv-cs-ro

Amplify What You Gaze At: Target Saliency Boosting in Text-to-Image Generation

arXiv:2609.30733v1 Announce Type: new Abstract: Text-to-image generation has advanced in controlling what, where, and how objects appear, yet how visual attention is distributed among objects remains

Anchor to Expand: Semantic Anchoring for Personalized Text-to-Image Diffusion Models

arXiv:2511.22245v2 Announce Type: replace Abstract: Personalizing text-to-image diffusion models extends pretrained models to represent novel user-specific concepts from only a few reference images. H

Attention-Based Adaptive Policies for Simultaneous Speech-to-Text Translation

arXiv:2609.30839v1 Announce Type: new Abstract: Simultaneous speech-to-text translation (Simul-S2TT) consists of generating partial translations while the incoming audio frames are processed by the sy

safetyarxiv-cs-lg

Audio LLMs Know When They Can't Hear You

arXiv:2609.30625v1 Announce Type: new Abstract: Audio large language models allow users to interact with the model through speech. When an input recording is too degraded, the model may misinterpret t

safetyarxiv-cs-ai

AuthGuard-R: Safety-Compliant Mission Hijacking and Dual-Gate Defense for LLM-Controlled Robots

model-releasesarxiv-cs-ro

arXiv:2609.31110v1 Announce Type: new Abstract: Large language models are increasingly used as high-level planners for mobile robots, robot manipulators, and autonomous vehicles. Recent studies show t

AYLA: Amplifying Gradient Sensitivity via Loss Transformation in Non-Convex Optimization

arXiv:2504.01875v3 Announce Type: replace Abstract: Stochastic Gradient Descent (SGD) and its variants, such as ADAM, are foundational to deep learning optimization, adjusting model parameters through

Benchmarking the Connectomes of Caenorhabditis elegans within the Reservoir Computing Framework

arXiv:2609.30508v1 Announce Type: new Abstract: The aim of this work is to examine the connectomes of Caenorhabditis elegans through a computational lens using the reservoir computing framework. Conne

Benchy: towards a universal language for task-oriented AI benchmarks

model-releasesarxiv-cs-ai

arXiv:2609.30550v1 Announce Type: new Abstract: Benchy is a semantic language and execution engine for benchmarking AI programs. A benchmark is completely specified by a program, a scoring function, a

CCRV-Bench: Constraint-Based Evaluation of Causal Reasoning in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.30979v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated excellent performance in visual tasks, but their visual causal reasoning capabilities still lack reliabl