Search: “models”

Scale Matters: Adaptive Granularity Selection for Cross-Species 3D Plant Organ Segmentation

arXiv:2608.17803v1 Announce Type: new Abstract: Recent 3D foundation models provide powerful feature representations for point cloud learning by controlling spatial granularity. However, relying on a

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Spectral Gradient Orthogonalization Improves Differentially Private Training at Scale

DGX agent

arXiv:2608.17415v1 Announce Type: new Abstract: Differentially private training adds isotropic Gaussian noise to clipped gradients, corrupting every singular direction equally. In vision models, where

safetyarxiv-cs-cv

19 Aug 2026

Tight Bounds for Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function

model-releasesarxiv-cs-lg

arXiv:2608.17343v1 Announce Type: new Abstract: Data-driven algorithm design frames hyperparameter tuning as a statistical learning problem, but establishing generalization guarantees remains challeng

Toward Personal Intelligence Through Cooperative Observation

arXiv:2608.17128v1 Announce Type: new Abstract: A personal AI system needs a model of the user's goals, constraints, and ongoing commitments to plan and act on their behalf, and the quality of that mo

researcharxiv-cs-ai

TRUSS: Towards Task-Reliable and User-Safe Automated Agent Skill Generation

arXiv:2608.17588v1 Announce Type: new Abstract: Agent Skills package reusable natural language procedures with executable resources, enabling software agents to acquire task specific capabilities with

When Agents Act on Web3: An Attack-Surface Survey of MCP, Skills, and Tool Calling

arXiv:2608.17275v1 Announce Type: cross Abstract: AI agents increasingly act rather than merely read: across the Model Context Protocol (MCP) ecosystem, the share of deployed tools that modify externa

safetyarxiv-cs-ai

When Writing Style Drifts: Benchmarking Authorship Verification under Distribution Shifts in Genre, Time and the AI-Era

model-releasesarxiv-cs-cl

arXiv:2608.17979v1 Announce Type: new Abstract: Authorship verification (AV) assumes that an author's writing style remains sufficiently stable to distinguish it from that of other writers. In practic

Tutorials

Which CS1 Students Will Fail? Identifying Digital Markers from Learning Analytics in Computer Systems and Architecture Using Weighted Academic Momentum and Interaction Logs

arXiv:2608.16914v1 Announce Type: cross Abstract: Digital learning platforms generate rich behavioural traces (digital markers) that offer the potential to identify struggling students early. This pap

tutorialsarxiv-cs-lg

Tutorials

A Blueprint for Equilibrium-Based Differentiable Continuous-Variable Thermodynamic Computing

arXiv:2607.16183v2 Announce Type: replace Abstract: To help address the escalating energy and latency demands of machine-learning workloads, we introduce a blueprint for an energy-efficient and fast t

tutorialsarxiv-cs-lg

A Scalable Pipeline for LLM-Teacher Distillation Labeling: Work-Stealing Job Scheduling and Memory-Aware GPU Concurrency

arXiv:2608.15975v1 Announce Type: cross Abstract: Labeling large text corpora with LLM teachers has become a practical route to training data at scale. At millions of items, hand-labeling every batch

A Temporal Planning Framework for Disruption Aware Dynamic Route Optimization in Heterogeneous Railway Systems

arXiv:2606.14582v2 Announce Type: replace Abstract: Efficient route optimization play a vital role in ensuring both safety and punctuality in railway operations. It is very crucial particularly in het

Agents

ALKEMIE Agent: an autonomous platform for computational materials design

arXiv:2608.15776v1 Announce Type: cross Abstract: Despite the powerful multi-scale modeling methods and high-throughput infrastructures established in the materials community, real material computatio

agentsarxiv-cs-ai

Agents

An Agentic Framework Using Rules and LLMs for Embedding and Annotating Descriptive Document Layouts: A Plant Science Use Case

arXiv:2608.14587v1 Announce Type: new Abstract: Background: Recent advances in information retrieval (IR) leverage both dense and sparse representations, large language models (LLMs), and specialized

agentsarxiv-cs-ai

An automatic-differentiation framework for time-lapse electrical resistivity tomography inversion of hydrologic dynamics

arXiv:2608.14661v1 Announce Type: new Abstract: Time-lapse electrical resistivity tomography (TL-ERT) provides spatially distributed information on subsurface hydrologic changes. However, inversion of

hardwarearxiv-cs-lg

Assessing AI-Generated vs. Human-Authored Spear Phishing SMS Attacks: An Empirical Study

arXiv:2406.13049v3 Announce Type: replace-cross Abstract: Personalized phishing is difficult to defend against because messages can be tailored to a target's work, interests, and social context. Large

AutoMem: A Text-Gradient Recursive Self-Improvement Framework for Automated Memory Architectures Search

arXiv:2608.14621v1 Announce Type: cross Abstract: Long-term memory is increasingly central to LLM agents, yet memory design remains a highly coupled architecture problem: what to encode, how to store

BASeg: Boundary-Aware Remote Sensing Segmentation with Structural Penalties

model-releasesarxiv-cs-cv

arXiv:2608.15683v1 Announce Type: new Abstract: Semantic segmentation is a core computer vision task in the remote sensing field, accelerating advancements in ur- ban development, agriculture, ecology

Belayer: Efficient Fault Tolerance for LLM Agentic RL Training

arXiv:2608.14635v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly trained with reinforcement learning in long-horizon, sandboxed environments. Unlike conventional RL

local-aiarxiv-cs-lg

Beyond Clear Skies: Synthetic Seasonal and Weather Variations for Real-World Drone Detection

model-releasesarxiv-cs-cv

arXiv:2608.16191v1 Announce Type: new Abstract: Reliable drone detection under real-world deployment conditions requires training data that spans the full operational design domain, including adverse

Beyond Uncertainty: Generalizable Failure Monitoring for Surgical Segmentation under Acquisition Degradation

arXiv:2608.16748v1 Announce Type: new Abstract: Surgical segmentation networks can fail silently under acquisition degradation: predicted masks may be wrong even when model confidence remains high. Ex

BRAID: Learning Equilibrium Maps in Interdependent Security Games via Weight-Tied Iterative Graph Neural Networks

model-releasesarxiv-cs-lg

arXiv:2608.14856v1 Announce Type: cross Abstract: Computing Nash equilibria in interdependent security (IDS) games on networks is computationally expensive: best-response dynamics may need hundreds of

Breaking and Defending LLM-Powered Social Media Bot Detection Systems

arXiv:2608.15893v1 Announce Type: new Abstract: The rise of social media bots poses a persistent threat, enabling misinformation, opinion manipulation, and the erosion of trust in online platforms. To

Broken Symmetry in LLM Refusal: Answer Release Is More Local Than Refusal Restoration

arXiv:2608.15772v1 Announce Type: new Abstract: When a language model refuses to answer a prompt, it is unclear whether the correct answer is erased from its internal representations, or merely suppre

local-aiarxiv-cs-ai

Calibrated Trust, Not Sharper Prediction: An Empirical Test of Uncertainty Fusion

arXiv:2608.14617v1 Announce Type: cross Abstract: A recurring proposal in legal AI is to improve case-outcome prediction by fusing uncertainty tools (evidence graphs with belief propagation, sequentia

Closing the Loop: A Control-Theoretic Framework for Provably Stable Time Series Forecasting with LLMs

arXiv:2602.12756v2 Announce Type: replace Abstract: Large Language Models (LLMs) have recently shown exceptional potential in time series forecasting (TSF), leveraging their inherent sequential reason

local-aiarxiv-cs-lg

Concept-based explanation of gene expression prediction from H&E images

arXiv:2608.16669v1 Announce Type: new Abstract: Recent advances in pathology foundation models have enabled accurate prediction of spatial transcriptomics (ST) from routine H&E images. However, existi

Decoupling Parcellation from Classification: Systematic Benchmark of Fast Brain Segmentation Methods for Alzheimer's Disease Detection

arXiv:2608.16039v1 Announce Type: cross Abstract: Brain parcellation and classification are typically evaluated in isolation, yet downstream AD detection performance depends on their interaction. We d

DirMixE: Harnessing Test Agnostic Long-tail Recognition with Hierarchical Label Variations

arXiv:2405.07780v3 Announce Type: replace-cross Abstract: This paper explores test-agnostic long-tail recognition, a challenging long-tail task where the test label distributions are unknown and arbit

Efficient Audio-Visual Generation via Synchrony-Aware Cross-Modal Sparse Attention

arXiv:2608.15522v1 Announce Type: new Abstract: Recent audio-visual generation models can synthesize synchronized video and sound in a unified diffusion process, but their inference cost remains high

Efficient Block-Layer Parallel Inference for Vision-Language-Action on Hybrid Architectures

arXiv:2608.14586v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are becoming a promising paradigm for autonomous driving, but their deployment on existing vehicle platforms remai

hardwarearxiv-cs-ai

ER-KANs: Efficient and Robust Kolmogorov-Arnold Networks for Data-Scarce Scientific Machine Learning

arXiv:2608.14773v1 Announce Type: cross Abstract: The efficient-KAN literature---covering Chebyshev, wavelet, and radial-basis-function variants of the original Kolmogorov-Arnold Network---has been be

Evaluating the trustworthiness of the Frechet Inception Distance with stochastic embedding representations

arXiv:2601.21979v2 Announce Type: replace Abstract: Feature embeddings acquired from pretrained models are widely used in medical applications of deep learning to assess the characteristics of dataset

researcharxiv-cs-lg

Every Expert Counts: ExactMoE for Memory-Efficient W4A16 Inference

arXiv:2608.15383v1 Announce Type: new Abstract: Sparse mixture-of-experts (MoE) language models reduce arithmetic by activating only a small subset of experts per token, yet deployment still requires

hardwarearxiv-cs-lg

Exact Attention Sensitivity and the Geometry of Transformer Stability

arXiv:2602.18849v2 Announce Type: replace-cross Abstract: We develop a sensitivity analysis for transformer attention in a geometry aligned with tokenwise computation. Our main result is the exact ide

FinFraudBench: A Heterogeneous Graph Benchmark for Financial Fraud Detection

arXiv:2608.15177v1 Announce Type: cross Abstract: The increasing complexity of digital financial systems has reshaped financial fraud detection from isolated transaction classification into relational

FLEET: Token-Based Feature Extraction for Event Camera-based Reinforcement Learning

model-releasesarxiv-cs-cv

arXiv:2608.16523v1 Announce Type: new Abstract: Event cameras generate asynchronous, high-frequency data streams offering spatially sparse information at lower latency than traditional cameras.In prin

FluxBin: Flexible LUT-based Ultra-low-bit LLM Inference by Algorithm-Kernel Synergy

arXiv:2608.15602v1 Announce Type: cross Abstract: While binary quantization theoretically promises extreme compression and acceleration for Large Language Models (LLMs), existing research often overlo

hardwarearxiv-cs-ai

From Sequence to Structure: Relational Uncertainty Propagation for LLM Agents

arXiv:2608.16002v1 Announce Type: cross Abstract: Reliable uncertainty quantification (UQ) is essential for deploying large language model (LLM) agents in complex interactive environments. Existing UQ

local-aiarxiv-cs-ai

Funnel of Thoughts: Efficient Test-Time Scaling via Early Voting and Rollout Pruning

arXiv:2608.15065v1 Announce Type: new Abstract: Large Reasoning Models produce diverse, sometimes inconsistent answers across repeated queries on the same problem, so multi-sample inference is a prere

researcharxiv-cs-ai

Geometric Self-Supervised Pre-training for Neural Combinatorial Optimization

arXiv:2608.00270v2 Announce Type: replace Abstract: Neural Combinatorial Optimization (NCO) techniques have emerged as a highly efficient alternative to traditional exact algorithms for solving routin

safetyarxiv-cs-ai

Geometry Is Not Robustness: A Trajectory-Level Study of PGD Evaluation

arXiv:2608.14594v1 Announce Type: new Abstract: Projected Gradient Descent (PGD) is widely used to evaluate adversarial robustness, typically via final adversarial accuracy, which does not capture mod

safetyarxiv-cs-lg

Graph Neural Assisted Actor-Critic for Latency-Efficient Edge Vision System

arXiv:2608.16142v1 Announce Type: cross Abstract: UAV on-board vision systems are widely used for different activities, including monitoring in no-fly zones. In this case, the vision-equipped UAV stre

researcharxiv-cs-ai

Grounding Robot Generalization in Training Data via Retrieval-Augmented VLMs

model-releasesarxiv-cs-ro

arXiv:2603.11426v3 Announce Type: replace Abstract: Recent work on robot manipulation has advanced policy generalization to novel scenarios. However, it is often difficult to characterize how differen

Applications

Handover Analysis for Vehicular Communication with Explainability on the Fly

arXiv:2608.14820v1 Announce Type: cross Abstract: Handover (HO) management in vehicular networks requires fast and reliable decision-making under highly dynamic conditions. While machine learning (ML)

applicationsarxiv-cs-ai

HarmTrace: Anchor-Calibrated Decoupled Optimization for Fine-Grained Target Identification in Harmful Memes

arXiv:2608.16622v1 Announce Type: cross Abstract: Multimodal harmful meme detection is typically formulated as image--text harmfulness classification. A model may correctly predict harmfulness while m

safetyarxiv-cs-ai

Harness the Memory: A Holistic Evaluation of Memory Substrates in Memory Agents

model-releasesarxiv-cs-cl

arXiv:2608.15008v1 Announce Type: new Abstract: Memory is becoming core infrastructure for long-horizon LLM agents, yet existing evaluations offer limited guidance on which memory substrate, namely th

Tutorials

Hide&Seek: Learning to Explain in an End-to-End Differentiable Network

arXiv:2608.16689v1 Announce Type: cross Abstract: Instance-wise feature selection is a valuable tool for interpreting labeled data and the predictions of black-box models. In contrast to global featur

tutorialsarxiv-cs-lg

HiPHI: A Large-Scale Benchmark for High-Precision Human Motion and Object-Interaction

arXiv:2608.16222v1 Announce Type: cross Abstract: Humanoid intelligence requires learning over an extremely diverse space of whole-body motions and physically grounded interactions. However, existing