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Behavioral Inference at Scale: The Fundamental Asymmetry Between Motivations and Belief Systems

model-releasesarxiv-cs-lg

arXiv:2509.05624v3 Announce Type: replace-cross Abstract: How much information about an agent's underlying values can be recovered from its observable behavior? This question matters for any approach

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Benchmarking LLM-Guided Control-Plane Policies for Backend Fault Isolation in HAProxy

DGX agent

arXiv:2608.10532v1 Announce Type: cross Abstract: Static load balancers cannot mitigate a backend that is degraded rather than down: round-robin and least-connections keep routing traffic to a server

model-releasesarxiv-cs-lg

12 Aug 2026

Benchmarking Time Series Generation Methods for Privacy-Preserving Forecasting

model-releasesarxiv-cs-lg

arXiv:2608.10891v1 Announce Type: new Abstract: Time series forecasting in privacy-sensitive domains often requires training models on released data rather than original observations. Synthetic time s

Beyond a Bag of Features: Set-Level Instability in Sparse Autoencoders

arXiv:2608.11197v1 Announce Type: cross Abstract: Shani et al. (2026) show that LLM representations broadly recover human category boundaries, while failing to reflect fine-grained typicality structur

researcharxiv-cs-cl

Beyond Decision Boundaries: Relational Geometry Attacks on Contrastive Embedding Manifolds

arXiv:2608.10237v1 Announce Type: new Abstract: Contrastive learning and Siamese embedding models have become the foundation of modern verification systems, where decisions are governed not by discret

Beyond Detection Accuracy: Measuring Explanation Cost, Stability, and Utility for Resource-Aware IoT Intrusion Detection

arXiv:2608.10349v1 Announce Type: cross Abstract: Machine-learning intrusion-detection studies commonly emphasize predictive accuracy while treating explanation generation as a computationally free po

Local Ai

Beyond Detection: Evaluating Defensive LLMs Against AI-Generated Social Engineering in Live Turn-by-Turn Interaction

arXiv:2608.10239v1 Announce Type: new Abstract: Generative AI makes social-engineering attacks more fluent, adaptive, and scalable, increasing the need for LLM-based de- fenders that can protect users

local-aiarxiv-cs-ai

Beyond Fixed Luminance: Towards Panchromatic and Orthochromatic Image Colorization

arXiv:2608.10798v1 Announce Type: cross Abstract: Most image colorization systems operate in Lab space by predicting chroma (ab) while preserving an input-derived luminance channel (L). While effectiv

Beyond Forecasting: Recasting Volatility Control as a Routing Problem

arXiv:2608.10375v1 Announce Type: cross Abstract: Volatility control converts risk estimates into portfolio exposure, yet existing approaches often rely on a fixed volatility estimator or a pre-define

safetyarxiv-cs-ai

Beyond Pixels: From Video Priors to 4D Worlds

arXiv:2608.10744v1 Announce Type: new Abstract: 4D generation synthesizes dynamic 3D scenes from conditions such as text or images. Existing methods either reconstruct generated RGB videos with a sepa

BooST: Bridging Semantics and Motions for Efficient Skill Transfer

arXiv:2608.10600v1 Announce Type: cross Abstract: Skill abstraction---the process of learning reusable and temporally extended behaviors---has emerged as a key paradigm for improving sample efficiency

safetyarxiv-cs-cv

Boundary-Seeking Policy Gradient for Safe Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2608.10204v1 Announce Type: new Abstract: Safe reinforcement learning maximizes reward subject to safety constraints. For Constrained Markov Decision Processes, the linear-programming view over

BPG: Balancing Plasticity and Generalization for Domain Incremental Learning

arXiv:2608.10804v1 Announce Type: cross Abstract: Deep neural networks excel in various tasks but struggle to generalize across evolving data distributions, leading to significant performance degradat

BREAD: Baseline-Referenced Explanations for Anomaly Diagnosis

arXiv:2608.10587v1 Announce Type: new Abstract: Artificial Intelligence (AI)-based prospective anomaly detection methods are increasingly deployed in high-dimensional and nonlinear settings. Among the

applicationsarxiv-cs-lg

BreastMammo and DenseMammo: Benchmarks for Mammography Domain Generalization

arXiv:2608.10271v1 Announce Type: cross Abstract: Breast density classification is a critical component of breast cancer risk assessment, yet AI models often struggle to generalize across clinical sit

Bridging Event Streams and DiT: Event-Guided Video Frame Interpolation

arXiv:2608.10479v1 Announce Type: new Abstract: Latent diffusion models have recently advanced video frame interpolation by synthesizing intermediate frames between input images. However, handling lar

Bridging Severe Cross-Modal Misalignment: End-to-End Visible-Infrared Object Detection via Explicit Feature-Domain Affine Registration

model-releasesarxiv-cs-cv

arXiv:2608.10680v1 Announce Type: new Abstract: Visible-infrared object detection relies on complementary RGB and thermal cues, but its performance is often degraded by cross-modal spatial misalignmen

CADET: Context-Conditioned Ads CTR Prediction With a Decoder-Only Transformer

arXiv:2602.11410v2 Announce Type: replace Abstract: Click-through rate (CTR) prediction is fundamental to online advertising systems. While Deep Learning Recommendation Models (DLRMs) with explicit fe

applicationsarxiv-cs-lg

Calibrating Post-Training Feature Shifts for LLM Data Contamination Detection

arXiv:2608.10462v1 Announce Type: new Abstract: Large language models (LLMs) are trained on massive and largely undisclosed corpora that may contain copyrighted or privacy-sensitive content. Data cont

researcharxiv-cs-cl

Tutorials

Can Bayesian Optimization Efficiently Find a Strong Single Expert in Neural Thickets?

arXiv:2608.10867v1 Announce Type: new Abstract: Gradient-free post-training has emerged as a compelling alternative to gradient-based optimization for large language models (LLMs), but existing approa

tutorialsarxiv-cs-lg

Can Computational Reducibility Lead to Transferable Models for Graph Combinatorial Optimization?

arXiv:2603.02462v2 Announce Type: replace-cross Abstract: A key challenge in developing unified neural solvers for combinatorial optimization (CO) is the efficient generalization of models from a give

Can Released LLM Vocabularies Support Token-Level Estimation of Hidden Corpora?

model-releasesarxiv-cs-cl

arXiv:2608.10690v1 Announce Type: new Abstract: Pretraining corpus composition shapes LLM capabilities, but it often remains hidden even when model weights are released. Prior work has inferred corpus

CapProbe: Evaluating Detailed Image Captions via Full-Scene Dense Question Answering

model-releasesarxiv-cs-cv

arXiv:2608.11074v1 Announce Type: new Abstract: Evaluating detailed image captions from Vision-Language Models (VLMs) requires going beyond surface-level semantic similarity. Reference-based metrics (

Capturing Uncertainty in Human Motion for Representation Learning in Soccer

arXiv:2608.11203v1 Announce Type: new Abstract: This paper presents a self-supervised representation learning framework for understanding 3D skeleton-based human motion in soccer, using future motion

Hardware

CARB: A Characterization-Guided Framework for CNN Inference Cost Prediction and Deployment Screening

arXiv:2608.10506v1 Announce Type: cross Abstract: Accurate pre-deployment estimation of CNN inference cost--energy, latency, and peak memory--is increasingly critical as models are deployed on resourc

hardwarearxiv-cs-lg

CARE: Confidence-Aware Reasoning for Reliable Medical VQA

arXiv:2608.10964v1 Announce Type: cross Abstract: Reinforcement Fine-Tuning (RFT) has enabled medical Multimodal Large Language Models (MLLMs) to produce Chain-of-Thought (CoT) reasoning for visual qu

safetyarxiv-cs-ai

Carefully Considering Culture: Analyzing LLM Alignment in Single- and Multi-Cultural Settings using Cultural Consensus Theory

arXiv:2608.09937v1 Announce Type: new Abstract: Recent work in NLP has probed large language models for their understanding of cultural norms across countries. However, this work typically considers d

safetyarxiv-cs-cl

CasDeblurGS: Cascaded 2D-to-3D Multi-View Consistency for 3D Gaussian Splatting from Two Blurry Images

arXiv:2608.10345v1 Announce Type: new Abstract: Free-viewpoint 3D scene media is increasingly important for immersive applications, yet practical capture often suffers from severe view sparsity and mo

applicationsarxiv-cs-cv

Causality Sum Rules in Conventional Scattering Matrices

arXiv:2608.10427v1 Announce Type: cross Abstract: Scattering matrices are the standard experimental and computational description of photonic and electromagnetic devices. Passivity is explicit in the

CausalSplat: Towards Comprehensive Hierarchical Reasoning in 3D Gaussian Splatting

arXiv:2608.11150v1 Announce Type: new Abstract: While 3D Gaussian Splatting (3DGS) has advanced open vocabulary scene understanding, existing methods remain confined to explicit queries. They struggle

Local Ai

Certify or Refuse: A Cross-Model Map for Selective Risk Control with Coverage Floors under Covariate Shift

arXiv:2608.10893v1 Announce Type: new Abstract: Certified selective predictors attain whatever coverage they attain; operators impose an automation floor: answer at least a eta-fraction of shifted tar

local-aiarxiv-cs-cl

Agents

Chain of Spatial Thoughts: Modality-Agnostic Spatial Grounding for Vision Language Models

arXiv:2608.10278v1 Announce Type: new Abstract: Spatial understanding is fundamental to embodied intelligence, underpinning applications such as robotic manipulation, embodied navigation, and autonomo

agentsarxiv-cs-cv

Chartography: A Benchmark for Professional Chart Understanding

model-releasesarxiv-cs-cv

arXiv:2608.10677v1 Announce Type: new Abstract: Professionals across medicine, engineering, finance, manufacturing, and the sciences often make consequential decisions from charts. Existing chart benc

Agents

ChemWorld: Programmable Chemical Worlds for Controlled and Replayable Agent Experimentation

arXiv:2608.10792v1 Announce Type: new Abstract: Autonomous chemistry increasingly depends on environments in which agents can repeatedly act, observe, and adapt.Physical laboratories provide essential

agentsarxiv-cs-ai

CHORUS: Complementary Experts for High-Coverage Testbench Stimulus Generation

arXiv:2608.10090v1 Announce Type: new Abstract: Large language models (LLMs) have advanced code generation, where executable feedback provides a more reliable learning signal than textual imitation al

ChronoSSM: Training for Temporally Aware Representations in Autoregressive State Space Models

arXiv:2608.10120v1 Announce Type: new Abstract: Modern sequence models, from Transformers to State Space Models, have enabled powerful generative modeling across diverse domains, yet they are typicall

Closed-Loop LLM Co-Pilots for Digital Agriculture

arXiv:2608.09949v1 Announce Type: new Abstract: This study evaluates the application of Large Language Models (LLMs) in complex biological systems, evolving from data analysis to autonomous, AI-guided

Closing a 17-Year Gap: Algorithmic Detection and Empirical Prevalence of Rank Reversal in Multi-Criteria Decision Analysis

arXiv:2508.00129v2 Announce Type: replace Abstract: Rank Reversal, where the relative order of alternatives changes in ways that violate axioms of rational decision-making, is a well-documented threat

applicationsarxiv-cs-ai

Agents

Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design

arXiv:2608.10299v1 Announce Type: new Abstract: Agentic systems are increasingly expected to improve after deployment, yet single-entity self-evolution is often bounded by a static learning context, s

agentsarxiv-cs-cl

ComBodied Agents: a New Paradigm of Human-Centric Agentic AI

arXiv:2608.10915v1 Announce Type: new Abstract: After an older adult misses a medication dose, a software agent can send another reminder and an embodied agent can bring the medication. Yet neither ex

Compact Feed-Forward 3D Gaussians via Saliency-Guided Primitive Merging

arXiv:2608.10712v1 Announce Type: new Abstract: 3D scene reconstruction, modeling, and rendering are highly relevant for numerous tasks, and 3D Gaussian splatting has become a standard choice in this

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition

arXiv:2608.10765v1 Announce Type: new Abstract: Recognizing human behavior across levels of abstraction, from atomic actions to long-horizon intentions, requires data annotated along a semantic hierar

Comprendia: AI-Augmented Code Comprehension

arXiv:2608.10290v1 Announce Type: cross Abstract: Comprendia is an Eclipse plugin that integrates structural dependency visualization with LLM-powered code explanation on a shared interactive graph fo

Compute-Optimal Is Not Cluster-Optimal: Systems-Aware Scaling for Sparse Mixture-of-Experts

arXiv:2608.10605v1 Announce Type: cross Abstract: In large-scale pretraining, the algorithm, architecture, and systems decisions are conventionally made in disconnected stages. A scaling law stage sel

Conditional Independence Tests for Constraint-Based Causal Discovery: A Survey

arXiv:2608.11156v1 Announce Type: cross Abstract: Conditional Independence (CI) tests are the statistical engine of constraint-based causal discovery: in algorithms such as PC (Peter-Clark) and FCI (F

Conflict or Strategy? Asymmetric Role Framing of La France insoumise and Rassemblement National in French News Headlines, 2022-2025

arXiv:2608.09936v1 Announce Type: new Abstract: Do French news headlines frame left- and right-populist challengers as symmetric ``extremes,'' or as fundamentally different political adversaries? We e

researcharxiv-cs-cl

ConfTriage: A Calibration-Aware LLM Triage Framework for Pulmonary Nodule Malignancy with Selective Specialist Deferral

arXiv:2608.10885v1 Announce Type: new Abstract: Pulmonary nodule malignancy prediction typically depends on image-trained specialist deep learning (DL) models that require substantial annotated imagin

safetyarxiv-cs-cv

ConRub-Med: Reinforcement Learning with Consensus Rubrics for Open-Ended Medical Question Answering

arXiv:2608.10996v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has been especially effective in mathematics and coding, where answers can be checked automatically. Many

safetyarxiv-cs-cl