Search: “models”

arepsilon-MemEvo: Adaptive Cross-Task Memory Transfer for LLM Program Evolution

arXiv:2608.12522v1 Announce Type: new Abstract: LLM-based program evolution systems such as FunSearch and AlphaEvolve have shown strong ability to discover novel algorithms, but typically optimize eac

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Research

Assessing the Effectiveness of Deep Embeddings for Tree Species Classification in the Dutch Forest Inventory

DGX agent

arXiv:2508.18829v3 Announce Type: replace Abstract: National Forest Inventory (NFI) serves as the primary source of forest information, however, maintaining these inventories requires labor-intensive

researcharxiv-cs-cv

14 Aug 2026

Auditable Agents

arXiv:2604.05485v2 Announce Type: replace Abstract: LLM agents call tools, query databases, delegate tasks, and trigger external side effects. Once an agent system can act in the world, the question i

DARTree: Speculative Diffusion Decoding with Autoregressive Draft Trees

arXiv:2608.13524v1 Announce Type: new Abstract: Speculative decoding losslessly accelerates autoregressive language models by verifying multiple draft tokens in parallel. Diffusion-based drafters furt

researcharxiv-cs-lg

Decentralized Multi-Player Q-Learning in Episodic Markov Decision Processes with Information Asymmetry

arXiv:2608.12753v1 Announce Type: new Abstract: We study decentralized multi-player reinforcement learning in episodic tabular Markov decision processes (MDPs) under three forms of information asymmet

Safety

Decoding Task Progress from VLA Representations

arXiv:2608.13474v1 Announce Type: new Abstract: Vision-language-action models (VLAs) are moving rapidly towards deployment as general-purpose manipulation policies, but we currently lack basic tools f

safetyarxiv-cs-ro

Delving into Cascaded Instability: A Lipschitz Continuity View on Image Restoration and Object Detection Synergy

model-releasesarxiv-cs-cv

arXiv:2510.24232v3 Announce Type: replace Abstract: To improve detection robustness in adverse conditions (e.g., haze and low light), image restoration is commonly applied as a pre-processing step to

Discovering Efficient and Explainable Communication Topologies for LLM-based Multi-Agent Systems via Causal Inference

arXiv:2608.12921v1 Announce Type: cross Abstract: The performance of large language model (LLM)-based multi-agent systems (MAS) largely depends on effective communication topologies. Existing topology

agentsarxiv-cs-ai

Dual-Manifold Geometry Guided Representation Learning: Adaptive Coupling between Kernel and Data Spaces

model-releasesarxiv-cs-cv

arXiv:2608.12737v1 Announce Type: new Abstract: Deep representation learning has primarily focused on how features evolve across network layers, while largely overlooking the structured geometry embed

Applications

Evaluating AlphaEarth Foundations Embeddings for Wildfire Susceptibility Mapping

arXiv:2608.12663v1 Announce Type: cross Abstract: Wildfire susceptibility mapping typically relies on physical variables assembled from multiple remote-sensing, climate, and geospatial products. Alpha

applicationsarxiv-cs-lg

Exploring Instruction Data Quality for Explainable Image Quality Assessment

arXiv:2510.03880v2 Announce Type: replace Abstract: In recent years, with the rapid development of large multimodal models (LMMs), explainable image quality assessment (IQA) has attracted increasing a

researcharxiv-cs-cv

FlowLOB: Efficient and Controllable Limit Order Book Generation with Flow Matching

arXiv:2608.13096v1 Announce Type: new Abstract: Limit order book (LOB) simulators are most useful to practitioners when they combine realistic market dynamics, computationally efficient sampling, cont

agentsarxiv-cs-lg

Foundations of Independent Component Analysis

arXiv:2608.13229v1 Announce Type: cross Abstract: We present the mathematical foundations of linear independent component analysis (ICA) models based on standard literature in a self-contained note. I

researcharxiv-cs-lg

Foundations of MT-PDCL: Measure-Theoretic Probabilistic Definite Clause Logic

arXiv:2608.13018v1 Announce Type: new Abstract: Standard probabilistic logic programming frameworks typically rely on grounding logic programs into discrete propositional representations. This operati

General Bayesian Policy Learning

arXiv:2602.23672v2 Announce Type: replace-cross Abstract: This study proposes a General Bayes framework for policy learning. We consider decision problems in which a decision-maker chooses an action f

Safety

Gradual Code-Switching as Inference-Time Cross-Lingual Representational Alignment for LLMs

arXiv:2510.05678v2 Announce Type: replace-cross Abstract: While large language models (LLMs) have achieved notable progress in multilingual settings, their performance remains uneven across languages

safetyarxiv-cs-ai

HC-RAG: Evidence-Centric Retrieval-Augmented Generation over Heterogeneous Financial Filings

model-releasesarxiv-cs-cl

arXiv:2608.12335v1 Announce Type: new Abstract: Financial question answering over annual reports requires more than retrieving semantically similar passages. It often involves identifying relevant com

History-informed Lagrangian Neural Networks

arXiv:2608.13215v1 Announce Type: new Abstract: Forecasting the long-horizon evolution of mechanical systems from position-only observations is a pivotal yet difficult task, as hidden velocities and t

HumanTracker: Towards Comprehensive and Human-Aligned Motion Tracking Benchmark

arXiv:2608.13555v1 Announce Type: cross Abstract: Humanoid motion tracking is central to teleoperation and whole-body imitation, yet evaluation often disagrees with what people perceive in videos. Kin

InFactPlanner: Planning Sustainable Geo-Distributed LLM Data Centers

arXiv:2608.12915v1 Announce Type: cross Abstract: The rapid growth of LLM inference is shifting sustainability concerns from one-time training to continuous serving, where infrastructure decisions sha

Large-scale Testing Global Optimization Methods with Black-box Adversarial Attacks

arXiv:2608.13296v1 Announce Type: cross Abstract: Existing global optimization benchmark suites are of a moderate size and are based on a small number of analytical functions that date back even to th

Local Ai

LLM-Assisted Dynamic Threat Analysis for Attacker-Reachable Software Weaknesses in Autonomous Vehicles

arXiv:2608.13450v1 Announce Type: cross Abstract: Autonomous vehicles depend on large safety-critical software stacks, where weaknesses reachable from adversarial inputs may affect steering, braking,

local-aiarxiv-cs-lg

Local Ai

LLMs Are Not Good Strategists, Yet Memory-Enhanced Agency Boosts Reasoning

arXiv:2608.12626v1 Announce Type: cross Abstract: Strategic reasoning in Large Language Models (LLMs) within long-horizon environments is often limited by inconsistent subgoals. In these settings, fin

local-aiarxiv-cs-ai

MatchMiner-AI: Open-source, Privacy-preserving Cancer Clinical Trial Matching using Artificial Intelligence

arXiv:2412.17228v4 Announce Type: replace Abstract: Background: Clinical trials are essential to advancing cancer treatments, but fewer than 10% of adults with cancer enroll in therapeutic trials. Ope

Minimax and Adaptive Covariance Matrix Estimation under Differential Privacy

arXiv:2603.19703v2 Announce Type: replace-cross Abstract: Estimating covariance matrices is fundamental to a wide range of statistical applications. This paper studies minimax and adaptive estimation

Local Ai

Multi-Agent Scheduling with LLM-Assisted Contract Net Negotiation for Stream Processing in Mobile Edge Computing

arXiv:2608.12371v1 Announce Type: new Abstract: Stream-processing systems increasingly operate across heterogeneous mobile edge--cloud infrastructures, where workload volatility, resource contention,

local-aiarxiv-cs-ai

Not All Nudges Land: Behavioral Controllability and Elaboration Quality in AI-Supported Journaling

arXiv:2608.12582v1 Announce Type: cross Abstract: AI journaling tools can tailor prompts to a person's own sensed behavior, but it is unclear which behaviors respond to them. We analyzed 369 journal e

On the Expressive Power of Transformers

arXiv:2608.12671v1 Announce Type: new Abstract: Multi-layer transformers form the critical component of essentially all large language models (LLMs) in use today. Because of their ubiquity and computa

On the Structural Limits of Machine Learning Decision Systems: An Information-Theoretic, Interaction-Based, and Stochastic-Dynamical Perspective

arXiv:2608.13510v1 Announce Type: cross Abstract: Machine learning procedures are commonly evaluated in terms of predictive accuracy and computational efficiency. However, their achievable performance

agentsarxiv-cs-lg

Applications

Optimizing Likelihoods via Mutual Information: Bridging Simulation-Based Inference and Bayesian Optimal Experimental Design

arXiv:2502.08004v2 Announce Type: replace-cross Abstract: Simulation-based inference (SBI) is a method to perform inference on a variety of complex scientific models with challenging inference (invers

applicationsarxiv-cs-lg

PIPES: Securing Agent Perception with Provenance and Priors

arXiv:2608.12789v1 Announce Type: cross Abstract: Tool-using agents consume external data from sources with different levels of trust, yet tool responses rarely identify who produced each component or

Predictive Allostatic Organization in Recurrent and Spiking Agents Under Partial Observability

arXiv:2608.11506v1 Announce Type: cross Abstract: Adaptive behavior under partial observability depends on internal organization that carries information beyond the current observation. Drawing on Bar

Prompts in the Wild: A Large Analyzed Collection of Transactional Prompts in Code

arXiv:2608.12905v1 Announce Type: new Abstract: The behavior of contemporary generative Large Language Models (LLMs) is directly shaped by prompts, unstructured texts that describe the desired output

researcharxiv-cs-cl

Robust data-driven discovery of fractional differential equations via weak formulations and Pareto-based subset selection

arXiv:2608.12879v1 Announce Type: new Abstract: Fractional partial differential equations describe nonlocal dynamics, but discovering them from noisy data is difficult because fractional differentiati

Robust Dempster-Shafer Evidence Fusion with Chaos-Conflict Measurement and Historical-Experience Weighting

arXiv:2608.13108v1 Announce Type: new Abstract: Multi-source evidence fusion under Dempster-Shafer theory faces two persistent challenges: existing conflict measures assess inter-evidence inconsistenc

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization

arXiv:2608.13538v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are proposed to extract numerous features from large language model (LLM) representations, yet explaining these features stil

researcharxiv-cs-cl

SCULPT: Subtractive Composition for 3D Part Generation

model-releasesarxiv-cs-cv

arXiv:2608.13541v1 Announce Type: new Abstract: Part-aware 3D generation aims to create digital assets that are coherent as complete objects while exposing structural parts for editing, material assig

Sign Language Video Synthesis via Loss-Guided Multi-Expert GANs

arXiv:2608.13368v1 Announce Type: cross Abstract: This preliminary technical report presents a framework for sign language video synthesis using a loss-guided multi-expert Generative Adversarial Netwo

@skills: Attention is all you have

arXiv:2608.12610v1 Announce Type: new Abstract: There are 56,804 public agent skills today, and teams write many more privately. The dominant delivery model is installation: once installed, a skill's

agentsarxiv-cs-ai

Tutorials

Sparse Orthogonal Regression Technique: A Spectral Framework for Equation Discovery, Approximation, and Integration

arXiv:2608.13504v1 Announce Type: new Abstract: We develop the Sparse Orthogonal Regression Technique (SORT), a sparse spectral framework for learning orthonormal-basis expansions from noisy and irreg

tutorialsarxiv-cs-lg

SSPO: Structure-Aware Similarity-Weighted Preference Optimization for Neural Combinatorial Optimization

arXiv:2608.12443v1 Announce Type: cross Abstract: Neural combinatorial optimization (NCO) relies on parallel solution sampling for training, yet existing methods fail to fully exploit the rich informa

The Hidden Evolution of Disguised Visual Context inside the VLM

arXiv:2606.20077v2 Announce Type: replace-cross Abstract: Visual tokens enter Large Language Models (LLMs) as raw, foreign signals. How they are transformed into meaningful representations and interac

Thought-Aware KV Cache Compaction for Reasoning via Adaptive Attention Matching

arXiv:2608.12331v1 Announce Type: cross Abstract: Reasoning language models generate lengthy chain-of-thought (CoT) sequences whose key-value (KV) cache grows linearly and becomes a memory bottleneck

TopoIntent: Compiling Security Intent into Executable, Compliance-Checked Network Topologies

arXiv:2608.13389v1 Announce Type: new Abstract: Enterprise security topology design requires translating business intent, regulatory requirements, and risk assumptions into zones, boundary devices, in

Training AI Scientists to Replicate Research

arXiv:2608.13331v1 Announce Type: cross Abstract: The replicability of papers is a cornerstone of scientific knowledge, ensuring the reliability of existing results and providing a base for further ex

Vero: Can AI Agents Build Formally Verified Software Repositories?

arXiv:2608.13522v1 Announce Type: cross Abstract: AI agents are increasingly used for programming, but do not provide any guarantee on the correctness of generated code. Verified code generation, in w

Safety

vToken: Token-Level Virtualization for Reclaimable KV Caches

arXiv:2608.13263v1 Announce Type: new Abstract: Large language model serving faces a critical memory bottleneck: the KV cache grows with sequence length and batch size. PagedAttention uses fixed-size

safetyarxiv-cs-ai

When Can You Trust Offline Evaluation of Equal-Cost Top-k Allocation? A Controlled, Reproducible Benchmark and Practitioner's Guide

arXiv:2608.12489v1 Announce Type: new Abstract: Organizations decide whom to treat under a budget and want to know what a targeting rule would have earned before deploying it. Off-policy evaluation pr