Search: “benchmark”

Algorithmic Compliance and Regulatory Loss in Digital Assets

arXiv:2603.04328v2 Announce Type: replace Abstract: We study the deployment performance of machine learning based enforcement systems used in cryptocurrency anti money laundering (AML). Using forward

applicationsarxiv-cs-lg

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Model Releases

Aligning Dense Retrievers with LLM Utility via DistillationAligning Dense Retrievers with LLM Utility via Distillation

DGX agent

arXiv:2604.22722v1 Announce Type: cross Abstract: Dense vector retrieval is the practical backbone of Retrieval- Augmented Generation (RAG), but similarity search can suffer from precision limitations

model-releasesarxiv-cs-ai

27 Apr 2026

An Interdisciplinary and Cross-Task Review on Missing Data Imputation

arXiv:2511.01196v3 Announce Type: replace-cross Abstract: Missing data is a fundamental challenge in data science, significantly hindering analysis and decision-making across a wide range of disciplin

applicationsarxiv-cs-ai

Anatomy-Aware Unsupervised Detection and Localization of Retinal Abnormalities in Optical Coherence Tomography

arXiv:2604.22139v1 Announce Type: new Abstract: Reliable automated analysis of Optical Coherence Tomography (OCT) imaging is crucial for diagnosing retinal disorders but faces a critical barrier: the

ArchSym: Detecting 3D-Grounded Architectural Symmetries in the Wild

arXiv:2604.22202v1 Announce Type: new Abstract: Symmetry detection is a fundamental problem in computer vision, and symmetries serve as powerful priors for downstream tasks. However, existing learning

ArmSSL: Adversarial Robust Black-Box Watermarking for Self-Supervised Learning Pre-trained Encoders

arXiv:2604.22550v1 Announce Type: cross Abstract: Self-supervised learning (SSL) encoders are invaluable intellectual property (IP). However, no existing SSL watermarking for IP protection can concurr

BERAG: Bayesian Ensemble Retrieval-Augmented Generation for Knowledge-based Visual Question Answering

arXiv:2604.22678v1 Announce Type: new Abstract: A common approach to question answering with retrieval-augmented generation (RAG) is to concatenate documents into a single context and pass it to a lan

researcharxiv-cs-cl

Bridging the Long-Tail Gap: Robust Retrieval-Augmented Relation Completion via Multi-Stage Paraphrase Infusion

model-releasesarxiv-cs-cl

arXiv:2604.22261v1 Announce Type: new Abstract: Large language models (LLMs) struggle with relation completion (RC), both with and without retrieval-augmented generation (RAG), particularly when the r

CAGE-SGG: Counterfactual Active Graph Evidence for Open-Vocabulary Scene Graph Generation

arXiv:2604.22274v1 Announce Type: new Abstract: Open-vocabulary scene graph generation (SGG) aims to describe visual scenes with flexible and fine-grained relation phrases beyond a fixed predicate voc

researcharxiv-cs-cv

Call-Chain-Aware LLM-Based Test Generation for Java Projects

arXiv:2604.22046v1 Announce Type: cross Abstract: Large language models (LLMs) have recently shown strong potential for generating project-level unit tests. However, existing state-of-the-art approach

CGC: Compositional Grounded Contrast for Fine-Grained Multi-Image Understanding

arXiv:2604.22498v1 Announce Type: cross Abstract: Although Multimodal Large Language Models (MLLMs) have advanced rapidly, they still face notable challenges in fine-grained multi-image understanding,

Chain-of-Memory: Lightweight Memory Construction with Dynamic Evolution for LLM Agents

arXiv:2601.14287v2 Announce Type: replace Abstract: External memory systems are pivotal for enabling Large Language Model (LLM) agents to maintain persistent knowledge and perform long-horizon decisio

researcharxiv-cs-lg

Tutorials

CLVAE: A Variational Autoencoder for Long-Term Customer Revenue Forecasting

arXiv:2604.22636v1 Announce Type: cross Abstract: Predicting customers' long-term revenue from sparse and irregular transaction data is central to marketing resource allocation in non-contractual sett

tutorialsarxiv-cs-lg

Cost-Effective Communication: An Auction-based Method for Language Agent Interaction

arXiv:2511.13193v2 Announce Type: replace Abstract: Multi-agent systems (MAS) built on large language models (LLMs) often suffer from inefficient 'free-for-all' communication, leading to exponential t

agentsarxiv-cs-ai

Data-Free Contribution Estimation in Federated Learning using Gradient von Neumann Entropy

arXiv:2604.22562v1 Announce Type: cross Abstract: Client contribution estimation in Federated Learning is necessary for identifying clients' importance and for providing fair rewards. Current methods

Decoding High-Dimensional Finger Motion from EMG Using Riemannian Features and RNNs

model-releasesarxiv-cs-lg

arXiv:2604.22499v1 Announce Type: new Abstract: Continuous estimation of high-dimensional finger kinematics from forearm surface electromyography (EMG) could enable natural control for hand prostheses

Decomposed Attention Fusion in MLLMs for Training-Free Video Reasoning Segmentation

arXiv:2510.19592v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) demonstrate strong video understanding by attending to visual tokens relevant to textual queries. To direct

researcharxiv-cs-cv

Deep Learning for Model Calibration in Simulation of Itaconic Acid Production

model-releasesarxiv-cs-lg

arXiv:2604.22496v1 Announce Type: new Abstract: In this study, deep learning is used to estimate kinetic parameters for modeling itaconic acid production based on real batch experiments conducted at d

Do Not Imitate, Reinforce: Iterative Classification via Belief Refinement

arXiv:2604.22110v1 Announce Type: new Abstract: Standard supervised classification trains models to imitate the exact labels provided by a perfect oracle. This imitation happens in a single pass, rest

agentsarxiv-cs-lg

DVGT-2: Vision-Geometry-Action Model for Autonomous Driving at Scale

arXiv:2604.00813v3 Announce Type: replace-cross Abstract: End-to-end autonomous driving has evolved from the conventional paradigm based on sparse perception into vision-language-action (VLA) models,

agentsarxiv-cs-ai

Efficient Diffusion Distillation via Embedding Loss

arXiv:2604.22379v1 Announce Type: new Abstract: Recent advances in distilling expensive diffusion models into efficient few-step generators show significant promise. However, these methods typically d

researcharxiv-cs-cv

EgoMAGIC- An Egocentric Video Field Medicine Dataset for Training Perception Algorithms

arXiv:2604.22036v1 Announce Type: cross Abstract: This paper introduces EgoMAGIC (Medical Assistance, Guidance, Instruction, and Correction), an egocentric medical activity dataset collected as part o

Emergent Strategic Reasoning Risks in AI: A Taxonomy-Driven Evaluation Framework

arXiv:2604.22119v1 Announce Type: new Abstract: As reasoning capacity and deployment scope grow in tandem, large language models (LLMs) gain the capacity to engage in behaviors that serve their own ob

Estimating Tail Risks in Language Model Output Distributions

arXiv:2604.22167v1 Announce Type: cross Abstract: Language models are increasingly capable and are being rapidly deployed on a population-level scale. As a result, the safety of these models is increa

EV-CLIP: Efficient Visual Prompt Adaptation for CLIP in Few-shot Action Recognition under Visual Challenges

arXiv:2604.22595v1 Announce Type: new Abstract: CLIP has demonstrated strong generalization in visual domains through natural language supervision, even for video action recognition. However, most exi

Fast, close, non-singular and property-preserving approximations of entropic measures

arXiv:2505.14234v2 Announce Type: replace-cross Abstract: Entropic measures like Shannon entropy (SE), its quantum mechanical analogue von Neumann entropy, and Kullback-Leibler divergence (KL) are key

researcharxiv-cs-ai

FeatEHR-LLM: Leveraging Large Language Models for Feature Engineering in Electronic Health Records

arXiv:2604.22534v1 Announce Type: cross Abstract: Feature engineering for Electronic Health Records (EHR) is complicated by irregular observation intervals, variable measurement frequencies, and struc

applicationsarxiv-cs-ai

FedSPDnet: Geometry-Aware Federated Deep Learning with SPDnet

arXiv:2604.22494v1 Announce Type: cross Abstract: We introduce two federated learning frameworks for the classical SPDnet model operating on symmetric positive definite (SPD) matrices with Stiefel-con

researcharxiv-cs-lg

FILTR: Extracting Topological Features from Pretrained 3D Models

arXiv:2604.22334v1 Announce Type: new Abstract: Recent advances in pretraining 3D point cloud encoders (e.g., Point-BERT, Point-MAE) have produced powerful models, whose abilities are typically evalua

Local Ai

Fine-Grained Analysis of Shared Syntactic Mechanisms in Language Models

arXiv:2604.22166v1 Announce Type: new Abstract: While language models demonstrate sophisticated syntactic capabilities, the extent to which their internal mechanisms align with cross-constructional pr

local-aiarxiv-cs-cl

FLARE-BO: Fused Luminance and Adaptive Retinex Enhancement via Bayesian Optimisation for Low-Light Robotic Vision

arXiv:2604.22093v1 Announce Type: new Abstract: Reliable visual perception under low illumination remains a core challenge for autonomous robotic systems, where degraded image quality directly comprom

GazeVLA: Learning Human Intention for Robotic Manipulation

arXiv:2604.22615v1 Announce Type: new Abstract: Embodied foundation models have achieved significant breakthroughs in robotic manipulation, yet they still depend heavily on large-scale robot demonstra

applicationsarxiv-cs-ro

HACHIMI: Scalable and Controllable Student Persona Generation via Orchestrated Agents

arXiv:2603.04855v3 Announce Type: replace Abstract: Student Personas (SPs) are emerging as infrastructure for educational LLMs, yet prior work often relies on ad-hoc prompting or hand-crafted profiles

agentsarxiv-cs-cl

Hidden Failure Modes of Gradient Modification under Adam in Continual Learning, and Adaptive Decoupled Moment Routing as a Repair

arXiv:2604.22407v1 Announce Type: cross Abstract: Many continual-learning methods modify gradients upstream (e.g., projection, penalty rescaling, replay mixing) while treating Adam as a neutral backen

researcharxiv-cs-ai

How Learning Rate Decay Wastes Your Best Data in Curriculum-Based LLM Pretraining

arXiv:2511.18903v2 Announce Type: replace-cross Abstract: Due to the scarcity of high-quality data, large language models (LLMs) are often trained on mixtures of data with varying quality levels, even

KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation

arXiv:2508.05633v2 Announce Type: replace-cross Abstract: Live streaming platforms have become a dominant form of online content consumption, offering dynamically evolving content, real-time interacti

LATMiX: Learnable Affine Transformations for Microscaling Quantization of LLMs

arXiv:2602.17681v2 Announce Type: replace-cross Abstract: Post-training quantization (PTQ) is a widely used approach for reducing the memory and compute costs of large language models (LLMs). Recent s

researcharxiv-cs-cl

LayerBoost: Layer-Aware Attention Reduction for Efficient LLMs

arXiv:2604.22050v1 Announce Type: cross Abstract: Transformers are mostly relying on softmax attention, which introduces quadratic complexity with respect to sequence length and remains a major bottle

researcharxiv-cs-cl

Learning Coverage- and Power-Optimal Transmitter Placement from Building Maps: A Comparative Study of Direct and Indirect Neural Approaches

model-releasesarxiv-cs-lg

arXiv:2604.22056v1 Announce Type: new Abstract: Optimal wireless transmitter placement is a central task in radio-network planning, yet exhaustive search becomes prohibitively expensive at scale. This

Learning from Natural Language Feedback for Personalized Question Answering

arXiv:2508.10695v2 Announce Type: replace-cross Abstract: Personalization is crucial for enhancing both the effectiveness and user satisfaction of language technologies, particularly in information-se

Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching

arXiv:2604.22061v1 Announce Type: cross Abstract: Patient-trial matching requires reasoning over long, heterogeneous electronic health records (EHRs) and complex eligibility criteria, posing significa

applicationsarxiv-cs-ai

LLMPhy: Parameter-Identifiable Physical Reasoning Combining Large Language Models and Physics Engines

arXiv:2411.08027v3 Announce Type: replace-cross Abstract: Most learning-based approaches to complex physical reasoning sidestep the crucial problem of parameter identification (e.g., mass, friction) t

LLMs as Assessors: Right for the Right Reason?

model-releasesarxiv-cs-cl

arXiv:2601.08919v2 Announce Type: replace-cross Abstract: A good deal of recent research has focused on how Large Language Models (LLMs) may be used as judges in place of humans to evaluate the qualit

Long-tail Internet photo reconstruction

arXiv:2604.22714v1 Announce Type: new Abstract: Internet photo collections exhibit an extremely long-tailed distribution: a few famous landmarks are densely photographed and easily reconstructed in 3D

Memanto: Typed Semantic Memory with Information-Theoretic Retrieval for Long-Horizon Agents

arXiv:2604.22085v1 Announce Type: new Abstract: The transition from stateless language model inference to persistent, multi session autonomous agents has revealed memory to be a primary architectural

agentsarxiv-cs-ai

Local Ai

mimo-v2.5 pro when

Xiaomi released and open-sourced MiMo-V2.5-Pro, delivering significant improvements over its predecessor in agentic capabilities, complex software engineering, and long-horizon tasks. The model is an

local-air-ollama

MolClaw: An Autonomous Agent with Hierarchical Skills for Drug Molecule Evaluation, Screening, and Optimization

arXiv:2604.21937v1 Announce Type: new Abstract: Computational drug discovery, particularly the complex workflows of drug molecule screening and optimization, requires orchestrating dozens of specializ

MTT-Bench: Predicting Social Dominance in Mice via Multimodal Large Language Models

arXiv:2604.22492v1 Announce Type: cross Abstract: Understanding social dominance in animal behavior is critical for neuroscience and behavioral studies. In this work, we explore the capability of Mult