Search: “models”

MetaKV: Adaptive KV Cache Compression for Constrained LLM Inference

arXiv:2609.07966v1 Announce Type: new Abstract: Key--value (KV) cache compression is an effective way to reduce the memory overhead of large language model (LLM) inference, particularly for long-conte

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MOAE: Multi-Objective Agent Evolution with Pareto-Preserving Search

DGX agent

arXiv:2609.05992v1 Announce Type: cross Abstract: As LLM-based agents continue to advance, their evaluation has become increasingly multifaceted: a capable agent must not only achieve high task comple

model-releasesarxiv-cs-lg

9 Sept 2026

Monotonic Kolmogorov-Arnold Networks: A Theoretical and Empirical Study of Monotonicity as an Inductive Bias

arXiv:2606.17886v3 Announce Type: replace Abstract: Monotonicity has been a long-running architectural inductive bias for neural networks, motivated by tabular, scientific, and economic settings where

Multi-Fidelity Physics-Informed Neural Networks with Bayesian Uncertainty Quantification and Adaptive Residual Learning for Efficient Solution of Parametric Partial Differential Equations

arXiv:2602.01176v2 Announce Type: replace Abstract: Physics-informed neural networks (PINNs) have emerged as a powerful paradigm for solving partial differential equations (PDEs) by embedding physical

NEO-BENCH: A New Multi-Source Benchmark for Generalizable Astronomical Streak Detection

arXiv:2609.06774v1 Announce Type: cross Abstract: Near-Earth Objects (NEOs) can appear as faint streaks in long-exposure astronomical images. Detecting these streaks across diverse observatories requi

Neural Posterior Estimation for Tomographic Weak Lensing Mass Mapping

arXiv:2609.07833v1 Announce Type: cross Abstract: Weak gravitational lensing shear and convergence trace the distribution of baryonic and dark matter across space, making them a powerful probe of cosm

researcharxiv-cs-cv

No-Regret Mixing of LRU and LFU with Optimal Switching Cost

arXiv:2609.07566v1 Announce Type: new Abstract: Caching systems often rely on simple eviction policies such as Least Recently Used (LRU) and Least Frequently Used (LFU), which perform well in compleme

Novel Methods for Catheter and Guidewire Segmentation in X-ray Fluoroscopy under a Federated Learning Setting

arXiv:2609.06876v1 Announce Type: new Abstract: Endovascular procedures rely on real-time manipulation of thin instruments, catheters and guidewires, under X-ray fluoroscopy guidance, where accurate v

Online, Reachability-Aware, Sampling-Based Motion Planning

arXiv:2609.09073v1 Announce Type: new Abstract: Sampling-Based Model-Predictive Control (MPC) algorithms are a flexible class of controllers used for navigation on a wide range of robotic systems. His

safetyarxiv-cs-ro

Optimal estimation for Functional Linear Regression with Noisy Discretized Data

arXiv:2609.08671v1 Announce Type: cross Abstract: In this paper, we consider the scalar-on-function linear regression model under a realistic sampling scheme in which the functional covariates are obs

OVMAN: A Task and Benchmark for Open-Vocabulary Motion-Aware Navigation

model-releasesarxiv-cs-ro

arXiv:2609.06424v1 Announce Type: new Abstract: Homes change between a robot's visits. Navigation benchmarks pose their goals in the world the agent currently sees, and the two-visit benchmarks that e

Parity, Sensitivity, and Transformers

arXiv:2602.05896v3 Announce Type: replace Abstract: Understanding what neural architectures can and cannot compute is a central challenge in the theory of AI. One of the fundamental problems in this c

Physical policy gradient theorem for in situ stochastic-adjoint training

arXiv:2609.05808v1 Announce Type: cross Abstract: In situ adjoint training extracts parameter gradients directly from measurement, but has so far been limited to reciprocal or restricted systems. Here

Programmable Cellular Automata

arXiv:2609.06102v1 Announce Type: cross Abstract: Cellular automata is a local computation paradigm where complex behavior can arise from local interactions between simple functions. This paradigm has

QGB-WkNN: Quantum Granular-Ball Learning for Robust Classification

arXiv:2609.05952v1 Announce Type: new Abstract: Nearest-neighbor classification is widely used in machine learning, yet existing methods often suffer from low computational efficiency and limited robu

RAH-VLA: Resolution-Adaptive Hierarchical Vision-Language Alignment for Multimodal Remote Sensing Understanding

arXiv:2512.23243v3 Announce Type: replace Abstract: Multimodal vision-language modeling has emerged as a promising paradigm for remote sensing (RS) image understanding. However, existing methods are l

safetyarxiv-cs-cv

RefGuard: Identity-Aware Language-Guided Robot Manipulation via Joint Target-Anchor-Frame Grounding

arXiv:2609.06221v1 Announce Type: new Abstract: Vision-language-action (VLA) models have substantially advanced language-guided robot manipulation, yet reliable execution still hinges on identifying w

safetyarxiv-cs-ro

Residual-augmented flow matching operators for probabilistic partial differential equations

arXiv:2512.12749v3 Announce Type: replace-cross Abstract: Learning surrogate models for physical systems with latent uncertainty remains challenging in data-scarce regimes: deterministic neural operat

safetyarxiv-cs-lg

Rethinking Learned Occupancy in Autonomous Active Mapping with Observation-Gated Filtering

arXiv:2609.09069v1 Announce Type: cross Abstract: Autonomous 3D active mapping requires a space robot to choose where to sense while building the geometry needed for navigation. Learned occupancy comp

Local Ai

Robust Decentralized Personalized Federated Learning via Prediction-Constrained Neighborhood Collaboration

arXiv:2609.07312v1 Announce Type: new Abstract: This paper proposes a robust decentralized personalized federated learning method R-DPFL, that enables clients to reduce the impact of Byzantine attacks

local-aiarxiv-cs-lg

Role-Specific Predictive Geometries for Nonstationary Multivariate Graph-Signal Forecasting

arXiv:2609.06519v1 Announce Type: new Abstract: Forecasting multivariate graph signals is challenging when node-level trajectories are nonstationary but stable relations persist across nodes and featu

Segment Any Motion with Radar: Robust Multimodal Moving-Object Segmentation and Tracking

arXiv:2609.08346v1 Announce Type: new Abstract: Moving-object perception must decide which image regions correspond to real motion and keep every instance identified over time. Methods that read motio

SeRV: Semantic-Aligned Residual Vector Quantization for American Sign Language Generation

arXiv:2609.05742v1 Announce Type: new Abstract: American Sign Language (ASL) generation remains challenging due to limited paired text-ASL motion data and the difficulty of learning motion representat

Sparse Gain Radio Map Reconstruction With Geometry Priors and Uncertainty-Guided Measurement Selection

arXiv:2604.05788v2 Announce Type: replace Abstract: Radio maps are important for environment-aware wireless communication, network planning, and radio resource optimization. However, dense radio map c

Stochastic Nonconvex Bilevel Optimization: Improved Rates Without Rare-Visit Assumption

arXiv:2609.06580v1 Announce Type: cross Abstract: We investigate stochastic simple bilevel optimization with smooth and possibly nonconvex upper- and lower-level objectives. Existing stochastic extens

Structurally Close, Temporally Distant: Measuring Security Exposure in Long-Horizon LLM Agents

arXiv:2609.05911v1 Announce Type: cross Abstract: Long-horizon LLM agents interact with untrusted content, persistent memory, external state, and sensitive tools. Existing analyses often characterize

TASG-Explore: Traversability-Aware Sector-Guided Exploration for Ground Robot on Uneven Terrain

model-releasesarxiv-cs-ro

arXiv:2609.08512v1 Announce Type: new Abstract: Autonomous exploration on uneven terrain requires ground robots to balance exploration efficiency, coverage completeness, and terrain safety. Detailed t

The BatchNorm Illusion: Diagnosing Normalization Artifacts in Machine Unlearning Evaluation

arXiv:2609.08901v1 Announce Type: new Abstract: Approximate machine unlearning aims to remove the influence of specific training data from a trained model without retraining from scratch. We identify

safetyarxiv-cs-lg

Think Wider: Mitigating Latent Rank Collapse in Implicit Chain-of-Thought Reasoning

arXiv:2609.07406v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning improves the reasoning ability of large language models by introducing intermediate computation, but explicit rationale

Tracing Mathematical Proficiency Through Problem-Solving Processes

arXiv:2512.00311v3 Announce Type: replace Abstract: Knowledge Tracing (KT) aims to model student's knowledge state and predict future performance to enable personalized learning in Intelligent Tutorin

TRAIL: Trajectory-Aware Visual Place Recognition against Unordered Databases

arXiv:2609.07373v1 Announce Type: new Abstract: Modern Visual Place Recognition (VPR) methods excel on standard benchmarks yet remain brittle in feature-poor environments. By treating each query image

Trust-But-Verify: Poisoning-Resilient Locally Private Graph Learning Protocols

arXiv:2609.07063v1 Announce Type: new Abstract: Built upon local differential privacy (LDP), locally private graph learning protocols have emerged as an important paradigm for decentralized graph lear

Unraveling the Real Working Mechanism and Inherent Flaws of GAE: A Method for Interpreting Transformer Processes from an Economic Perspective

arXiv:2609.07213v1 Announce Type: cross Abstract: We observe a phenomenon that current algorithmic research in the field of explainable artificial intelligence primarily pursues better performance on

researcharxiv-cs-cv

Visible-Reachable Workspace for Perception-Aware Humanoid Design

model-releasesarxiv-cs-ro

arXiv:2609.08905v1 Announce Type: new Abstract: Workspace analysis measures where a robot can place its end effector. For visually guided manipulation, reachability alone is insufficient: a kinematica

Visual Search Augmented Chain-of-Thought Reasoning for Attribute Value Extraction from Product Videos

arXiv:2609.06410v1 Announce Type: cross Abstract: Existing approaches to visual attribute value extraction (AVE) primarily rely on static product images, failing to capture temporal cues, multi-angle

researcharxiv-cs-cv

When Retain Constraints Conflict: Mitigating Forget-Retain Interference in Tabular Data

arXiv:2609.06786v1 Announce Type: new Abstract: Machine unlearning aims to remove the influence of designated training data while preserving model utility, but its behavior on tabular data remains und

When Speech Meets Lips: Interpretable Audio-Visual Synchronization for L2 Pronunciation Assessment

arXiv:2609.06788v1 Announce Type: new Abstract: Automatic Pronunciation Assessment (APA) systems have achieved strong performance with transformer-based models and self-supervised speech representatio

safetyarxiv-cs-cv

Local Ai

When Topology Betrays Privacy: Lattice-Based Reconstruction Attacks on Secure Aggregation in Decentralized Federated Learning

arXiv:2609.08476v1 Announce Type: cross Abstract: Secure Aggregation (SA) is widely regarded as a strong defense against model-update leakage in Federated Learning (FL), as it reveals only aggregate r

local-aiarxiv-cs-lg

Tutorials

A Comparative Study of Counterfactual Explainers for Graph Neural Networks Enabling Multiple Types of Graph Edit

arXiv:2609.05113v1 Announce Type: new Abstract: Counterfactual explanations for graph-structured data seek to determine minimal and realistic modifications required in an input graph to alter a model'

tutorialsarxiv-cs-lg

A Cost-Aware Agentic Architecture for NL-to-SQL over Nested Enterprise Schemas, with a New Benchmark

model-releasesarxiv-cs-ai

arXiv:2609.04641v1 Announce Type: new Abstract: Natural-language-to-SQL systems have ad- vanced rapidly on academic benchmarks, yet production enterprise schemas exhibit graph- like, semi-structured,

Hardware

A Sim-to-Real Study of Surface-Code Decoder Benchmarking

arXiv:2609.04557v1 Announce Type: cross Abstract: Quantum error-correction decoders are typically benchmarked against synthetic circuit-level noise, under the assumption that a decoder's ranking under

hardwarearxiv-cs-lg

A Verifier-Guided Explainable Reasoning Framework with Gold-Anchored QLoRA, Task-Aware Mixture-of-Experts, and Group-Relative RLVR

arXiv:2609.05221v1 Announce Type: cross Abstract: Large language models (LLMs) show strong reasoning ability, but their explanations can remain inconsistent, weakly grounded, or difficult to verify. W

safetyarxiv-cs-ai

Tutorials

Attention-guided super-resolution of 4D flow MRI in carotid arteries

arXiv:2609.04891v1 Announce Type: cross Abstract: Four-dimensional (4D) flow magnetic resonance imaging (MRI) is a powerful non-invasive technique for visualizing and quantifying complex blood flow pa

tutorialsarxiv-cs-ai

BEAM3R: Beam's-eye-view architecture with Mamba-3 for implicit dose reconstruction

arXiv:2609.04747v1 Announce Type: cross Abstract: To enable accurate and rapid photon control point and proton beamlet dose calculation in the DoseRAD2026 challenge, we present BEAM3R, a dose estimati

safetyarxiv-cs-cv

Beneath the Surface of Chains-of-Thought: A Mechanistic Interpretation of Reasoning Operations in LLMs

arXiv:2609.04753v1 Announce Type: new Abstract: Reasoning in large language models unfolds through diverse functional operations, such as problem formulation, goal decomposition, and deduction. Althou

safetyarxiv-cs-cl

Beyond Aggregate Scores: Behavioral Correctness Assumptions for Assessing Reference-Based Automatic Evaluation Methods

model-releasesarxiv-cs-ai

arXiv:2609.05289v1 Announce Type: new Abstract: Automated reference-based evaluation methods play a critical role in assessing natural language generation systems. Existing meta-evaluation primarily m

Hardware

Cache-Aware Joint Router Adaptation for Memory-Efficient MoE Inference

arXiv:2609.04895v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models activate only a small subset of experts per token, but the full expert set often exceeds GPU memory, causing repeated we

hardwarearxiv-cs-cl

Collaborative On-Sensor Array Cameras

arXiv:2506.04061v1 Announce Type: cross Abstract: Modern nanofabrication techniques have enabled us to manipulate the wavefront of light with sub-wavelength-scale structures, offering the potential to