Search: “inference”

PHBA: Prefix-State Hybrid Block Attention

arXiv:2610.08527v1 Announce Type: new Abstract: Hybrid architectures combining linear sequence models with softmax attention provide an effective balance between efficient long-context modeling and pr

local-aiarxiv-cs-lg

Applications

Polar: LLM-Powered Synthesis of Real-World Cyber Evidence for Prioritization and Mitigation

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DGX agent

arXiv:2610.07298v1 Announce Type: cross Abstract: Cyber threat analysis increasingly depends on evidence distributed across vendor advisories, vulnerability databases, and threat intelligence sources.

applicationsarxiv-cs-ai

7 Oct 2026

Applications

Practical Feasibility of Gradient Inversion Attacks in Federated Learning

arXiv:2508.19819v3 Announce Type: replace-cross Abstract: Gradient inversion attacks are often presented as a serious privacy threat in federated learning, with recent work reporting increasingly stro

applicationsarxiv-cs-ai

ProCut: Probabilistic Cutting Topology for Autonomous Electrosurgical Tissue Dissection

arXiv:2610.07515v1 Announce Type: new Abstract: Accurately modeling and tracking the deformation of soft tissue is critical for a wide range of interventional and surgical procedures. However, current

agentsarxiv-cs-ro

PRUE: A Practical Recipe for Field Boundary Segmentation at Scale

arXiv:2603.27101v2 Announce Type: replace Abstract: Large-scale maps of field boundaries are essential for agricultural monitoring tasks. Existing deep learning approaches for satellite-based field ma

Quantifying the Gap between Understanding and Generation within Unified Multimodal Models

model-releasesarxiv-cs-cl

arXiv:2602.02140v2 Announce Type: replace Abstract: Recent advances in unified multimodal models (UMM) have demonstrated remarkable progress in both understanding and generation tasks. However, whethe

RA-MoWE: Workflow-Affinity Embeddings for Query Clustering and Agentic Workflow Generation

arXiv:2610.07851v1 Announce Type: new Abstract: Agentic workflows enable large language models (LLMs) to solve complex tasks by coordinating reasoning, tool use, and verification. However, a workflow

RADC: Risk-Aware Dual Caching for Vision-Language Test-Time Adaptation

arXiv:2610.06932v1 Announce Type: new Abstract: Cache-based test-time adaptation (TTA) for vision-language models is often hindered by background bias in global representations and unreliable entropy-

safetyarxiv-cs-cv

Reactive Task-Oriented Robot-Human Handovers via Generative Hypothesis Selection

arXiv:2610.08003v1 Announce Type: new Abstract: When humans hand each other objects, they incorporate both geometric and semantic information into this process. For example, passing a knife with the h

researcharxiv-cs-ro

RefRoute: Decoupling Conditioning Cost from References via Compact Residual Conditioning and Spatial Routing

arXiv:2610.07720v1 Announce Type: new Abstract: Multi-reference image generation requires preserving the appearance of multiple subjects while composing them into a coherent scene. However, existing d

Rethinking Visual Provenance: Detection and Watermarking Across Direct Visual Generation and LLM-Driven Code Rendering

arXiv:2610.08137v1 Announce Type: cross Abstract: AI systems create images and videos with image/video generation models or by writing code and graphics descriptions that are then rendered. These rout

Risk-Sensitive Crowd Navigation with Adaptive Ellipsoidal Conformal Prediction

arXiv:2610.07474v1 Announce Type: new Abstract: Safe crowd navigation under distribution shift requires uncertainty representations that capture structured human-motion prediction errors and safety ob

safetyarxiv-cs-ro

Robust Importance Sampling for Rare Events via Constrained Gaussian Mixtures

arXiv:2610.07485v1 Announce Type: new Abstract: We study estimating rare-event probabilities I = P(g(mathbf{X}) > gamma) with mathbf{X} sim N(oldsymbol{mu}, oldsymbol{Sigma}) and general g : R^d o R.

RSJEV: Discriminative Remote Sensing Scene Classification with Multimodal Large Language Models

arXiv:2610.08539v1 Announce Type: new Abstract: Remote sensing scene classification is a fundamental task in Earth observation and geospatial analysis. Existing approaches mainly follow three paradigm

Scalable next-scale autoregression for medical image generation across anatomical regions

arXiv:2602.14512v3 Announce Type: replace Abstract: Autoregressive pretraining has been key to the scalability of large language models, yet medical generative foundation models remain predominantly b

researcharxiv-cs-cv

Selective Critique for Cost-Aware LLM Agents in Long-Horizon Decision Making

arXiv:2610.07335v1 Announce Type: cross Abstract: Improving the reliability of large language model (LLM) agents in long-horizon decision-making remains a key challenge. When deployed as autonomous ag

local-aiarxiv-cs-ai

Self-Retrospection Distillation: Turning Post-hoc Experiences into Prior Foresight

arXiv:2610.08077v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) turns agent experience into learning signals primarily through scalar outcome rewards after intera

safetyarxiv-cs-ai

ServeLearnBench: How Well Can Agents Self-Improve from Serving Experience?

model-releasesarxiv-cs-ai

arXiv:2610.07792v1 Announce Type: cross Abstract: Large language model agents are increasingly deployed to perform complex tasks in real-world environments. However, the knowledge required for correct

SkillFormer: Skill-Decomposed Adaptation for Audio Language Models

arXiv:2610.07533v1 Announce Type: cross Abstract: Audio language models must handle dozens of distinct skills, from pitch comparison and speaker counting to musical tempo estimation and emotion recogn

Small Language Models for Smart Data Model Classification at the Edge: A Cost-Aware Hybrid Approach

arXiv:2610.07093v1 Announce Type: new Abstract: The rapid proliferation of heterogeneous data sources within the Internet of Things (IoT) across domains such as smart cities, energy management, and en

researcharxiv-cs-ai

Tutorials

Source-Learned Reliance for Selective Test-Time Adaptation of Multimodal Time Series

arXiv:2610.07499v1 Announce Type: new Abstract: Multimodal wearable systems must remain reliable when sensor streams become noisy or unavailable. Existing multimodal test-time adaptation (TTA) methods

tutorialsarxiv-cs-lg

Sparse2comm: Towards Robust Cooperative 3D Object Detection

arXiv:2610.08573v1 Announce Type: new Abstract: Cooperative perception improves autonomous driving by sharing complementary observations among vehicles and roadside infrastructure for 3D object detect

safetyarxiv-cs-cv

SPECTRUM: Proximal Spectral Modulation for Looped Self-Distillation

arXiv:2610.07237v1 Announce Type: new Abstract: A model that learns from its own outputs inherits more than their correctness: it inherits which solutions it produces. We formulate Looped Self-Distill

researcharxiv-cs-ai

ST-Bench: A Spatial-Temporal Benchmark for Multi-Agent System Generation on Scientific Research Tasks

model-releasesarxiv-cs-ai

arXiv:2610.07763v1 Announce Type: new Abstract: The rapid progress of LLM-based multi-agent systems (MAS) has shown that they largely outperform single agents on coding, math, and QA tasks, where exec

Tutorials

Stochastic Siamese MAE Pretraining for Longitudinal Medical Images

arXiv:2512.23441v2 Announce Type: replace-cross Abstract: Temporally aware image representations are crucial for capturing disease progression in 3D volumes of longitudinal medical datasets. However,

tutorialsarxiv-cs-cv

Structured but Silent: Probing Capability Requirements in LLM Hidden States

arXiv:2610.08018v1 Announce Type: new Abstract: Reliable tool use requires more than triggering a mechanism or matching a query to an API description. Before selecting a specific tool, an agent must f

agentsarxiv-cs-cl

Structuring MoE Expert Selection for Agentic Reinforcement Learning

arXiv:2610.07332v1 Announce Type: cross Abstract: Long-horizon LLM agents are frequently implemented using sparse mixture-of-experts (MoE) models, yet the co-design of agentic behavior and MoE structu

agentsarxiv-cs-cl

Hardware

T-CCL: Resource Efficient and Performant Collective Communication using Tensor Memory Accelerator

arXiv:2610.07098v1 Announce Type: cross Abstract: Large transformer-based models increasingly depend on multi-GPU execution, which requires frequent collective communication among GPUs. Existing commu

hardwarearxiv-cs-ai

TabiBERT: A Large-Scale ModernBERT Foundation Model and A Unified Benchmark for Turkish

model-releasesarxiv-cs-cl

arXiv:2512.23065v4 Announce Type: replace Abstract: The introduction of BERT established encoder-only transformer models as a foundational paradigm in natural language processing. Encoder-only models

Text2Dashboard: A Governed Agent Architecture for Natural-Language Dashboard Generation over Enterprise DataBrain

arXiv:2610.06914v1 Announce Type: new Abstract: Text2Dashboard is a DataBrain-specific prototype that turns natural-language analytic requests into inspectable dashboards. An installable Codex plugin

TICDA: Tabular In-Context Data Attribution

model-releasesarxiv-cs-ai

arXiv:2610.07996v1 Announce Type: cross Abstract: Tabular foundation models (TFMs) achieve strong predictive performance by conditioning on labeled demonstrations provided in context, without any para

Towards benchmarking Western Bluebird detection in the wild

arXiv:2610.07802v1 Announce Type: new Abstract: Bird monitoring in natural environments is challenging due to the small size of some species of birds relative to the scene, background clutter, variabi

Trajectory-Retrieval Speculative Decoding: When Does a Model's Own History Help?

arXiv:2610.07350v1 Announce Type: new Abstract: Long chain-of-thought reasoning increases sequential decoding cost while creating a growing history of potentially reusable continuations. We investigat

local-aiarxiv-cs-ai

Transect: Retaining Observability for Long-Horizon LLM Agent Evaluations

arXiv:2610.08364v1 Announce Type: new Abstract: Frontier AI evaluations increasingly use open-ended, agentic, long-horizon tasks whose transcripts can span hundreds of pages of outputs and actions fro

Trustworthy Method Comparison with AI Judges: Estimation and Design under Order, Batch, and Aggregation Effects

arXiv:2610.07755v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as judges for automated AI evaluation. A common practice is to randomize prompt sequences and avera

Understanding Errors in LLM-Based Question Answering over Imperfect Tables

arXiv:2610.04687v2 Announce Type: replace Abstract: Answering questions over imperfect tables requires handling errors that can affect the answer. We investigate two challenges for large language mode

agentsarxiv-cs-cl

UniCounting: Instance-Aware Proposal Consolidation for Image-Query-Free Multi-Category Counting

arXiv:2610.08379v1 Announce Type: new Abstract: Visual counting is commonly formulated as counting a single specified target, with a model receiving an image-specific exemplar, text query, or target c

VLA-ACL: Action-Consistent Visual Token Pruning for Efficient Vision-Language-Action Models

arXiv:2610.08133v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models achieve strong robotic manipulation performance but incur high computational costs from processing long token sequ

safetyarxiv-cs-cv

WASD: Wasserstein-based Knowledge Distillation for Large Language Models

arXiv:2610.07706v1 Announce Type: cross Abstract: Autoregressive large language models (LLMs) have rapidly advanced in capability, but their increasing scale comes with substantial computational and m

safetyarxiv-cs-ai

Hardware

WavePrune: One period is often enough for RoPE

arXiv:2610.06963v1 Announce Type: new Abstract: Rotary Position Embedding (RoPE) encodes token positions by rotating each two-dimensional channel of the query and key vectors at a channel-specific fre

hardwarearxiv-cs-cl

When to Remember, When to Abstain: Category-Conditioned Retention for Reliable Agent Memory

arXiv:2610.07100v1 Announce Type: new Abstract: Persistent agent memory is only as reliable as its retention decision: an assertion weakly supported by its source can be stored and later reused as est

When to Rethink: Learning Multi-Perspective Self-Verification for Vision-Language Models

arXiv:2610.07018v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong performance in multimodal reasoning, yet they remain prone to generating plausible but incorrect answ

researcharxiv-cs-ai

Wiki-Talkie: Multilingual Benchmarking of Persona-Based Agents on Real-World Discussions

arXiv:2610.08513v1 Announce Type: cross Abstract: LLMs are increasingly deployed as autonomous agents in social environments, making it critical to study their ability to faithfully simulate human int

WiSPER: Pose-Supervised Predictive and Residual Flow Refinement For Multi-Person 3D Pose Estimation With WiFi CSI

arXiv:2610.07025v1 Announce Type: new Abstract: Multi-person 3D pose estimation with WiFi channel state information (CSI) is challenging because reflections from different people overlap without direc

local-aiarxiv-cs-cv

A Unified Dynamics Framework for Reinforcement Learning and Classical Control of a Six-DOF Pipeline-Tracking ROV in NVIDIA Isaac Sim

arXiv:2610.04949v1 Announce Type: new Abstract: Reinforcement learning controllers for underwater vehicles are usually trained against one physics representation and deployed against another, so repor

safetyarxiv-cs-ro

ALoDLM: Adaptively Looped Diffusion Language Models

model-releasesarxiv-cs-lg

arXiv:2610.04198v1 Announce Type: cross Abstract: Diffusion language models (DLMs) enable fast generation by predicting multiple tokens in parallel, but their practical adoption remains limited by a p

AnchorGen: Anchored Optimization for Customizable Generative 3D Design

arXiv:2610.06135v1 Announce Type: new Abstract: Engineering design often starts from a 2D sketch that fixes style and proportions, yet the subsequent 3D shape optimization relies on learned generative

researcharxiv-cs-cv

Anlu: Enabling In-Context Time Series Anomaly Detection in Foundation Models via Counterfactual Supervision

arXiv:2610.06180v1 Announce Type: new Abstract: Whether a time-series pattern is anomalous often depends on the operating regime of the monitored process. A missing event can signal a fault in one reg