Search: “benchmark”

Reduced NEXI protocol for the quantification of human gray matter microstructure on the Connectome 2.0 scanner

arXiv:2509.09513v2 Announce Type: replace-cross Abstract: Biophysical diffusion MRI models like Neurite Exchange Imaging (NEXI) are essential for probing gray matter microstructure, estimating compart

Human

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Research

Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling

DGX agent

arXiv:2604.28075v1 Announce Type: cross Abstract: Recent research has shown that filtering massive English web corpora into high-quality subsets significantly improves training efficiency. However, fo

researcharxiv-cs-ai

1 May 2026

Representative Spectral Correlation Network for Multi-source Remote Sensing Image Classification

arXiv:2604.27323v1 Announce Type: cross Abstract: Hyperspectral image (HSI) and SAR/LiDAR data offer complementary spectral and structural information for land-cover classification. However, their eff

RIHA: Report-Image Hierarchical Alignment for Radiology Report Generation

arXiv:2604.27559v1 Announce Type: cross Abstract: Radiology report generation (RRG) has emerged as a promising approach to alleviate radiologists' workload and reduce human errors by automatically gen

RoadMapper: A Multi-Agent System for Roadmap Generation of Solving Complex Research Problems

arXiv:2604.27616v1 Announce Type: new Abstract: People commonly leverage structured content to accelerate knowledge acquisition and research problem solving. Among these, roadmaps guide researchers th

ScaleBox: Enabling High-Fidelity and Scalable Code Verification for Large Language Models

arXiv:2604.27467v1 Announce Type: cross Abstract: Code sandboxes have emerged as a critical infrastructure for advancing the coding capabilities of large language models, providing verifiable feedback

SCOPE-FE: Structured Control of Operator and Pairwise Exploration for Feature Engineering

model-releasesarxiv-cs-lg

arXiv:2604.27025v1 Announce Type: cross Abstract: Automatic feature engineering is an effective approach for improving predictive performance in tabular learning. However, expand-and-reduce methods, s

Skills-Coach: A Self-Evolving Skill Optimizer via Training-Free GRPO

arXiv:2604.27488v1 Announce Type: new Abstract: We introduce Skills-Coach, a novel automated framework designed to significantly enhance the self-evolution of skills within Large Language Model (LLM)-

Softmax-GS: Generalized Gaussians Learning When to Blend or Bound

arXiv:2604.27437v1 Announce Type: new Abstract: 3D Gaussian Splatting (3D GS) is widely adopted for novel view synthesis due to its high training and rendering efficiency. However, its efficiency reli

Agents

SpaAct: Spatially-Activated Transition Learning with Curriculum Adaptation for Vision-Language Navigation

arXiv:2604.27620v1 Announce Type: new Abstract: Vision-and-Language Navigation (VLN) aims to enable an embodied agent to follow natural-language instructions and navigate to a target location in unsee

agentsarxiv-cs-cv

Spectral Dynamic Attention Network for Hyperspectral Image Super-Resolution

arXiv:2604.27326v1 Announce Type: cross Abstract: Hyperspectral image super-resolution is essential for enhancing the spatial fidelity of HSI data, yet existing deep learning methods often struggle wi

Static Program Slicing Using Language Models With Dataflow-Aware Pretraining and Constrained Decoding

arXiv:2604.26961v1 Announce Type: cross Abstract: Static program slicing is a fundamental software engineering technique for isolating code relevant to specific variables. While recent learning-based

Taming Noise-Induced Prototype Degradation for Privacy-Preserving Personalized Federated Fine-Tuning

arXiv:2604.27833v1 Announce Type: new Abstract: Prototype-based Personalized Federated Learning (ProtoPFL) enables efficient multi-domain adaptation by communicating compact class prototypes, but dire

researcharxiv-cs-cv

Targeted Linguistic Analysis of Sign Language Models with Minimal Translation Pairs

arXiv:2604.27232v1 Announce Type: new Abstract: Models of sign language have historically lagged behind those for spoken language (text and speech). Recent work has greatly improved their performance

Taxon: Hierarchical Tax Code Prediction with Semantically Aligned LLM Expert Guidance

arXiv:2601.08418v2 Announce Type: replace-cross Abstract: Tax code prediction is a crucial yet underexplored task in automating invoicing and compliance management for large-scale e-commerce platforms

Local Ai

TeD-Loc: Text Distillation for Weakly Supervised Object Localization

arXiv:2501.12632v2 Announce Type: replace Abstract: Weakly supervised object localization (WSOL) models are trained using only image-level class labels. They can predict both the object class and spat

local-aiarxiv-cs-cv

The Inverse-Wisdom Law: Architectural Tribalism and the Consensus Paradox in Agentic Swarms

arXiv:2604.27274v1 Announce Type: new Abstract: As AI transitions toward multi-agent systems (MAS) to solve complex workflows, research paradigms operate on the axiomatic assumption that agent collabo

TiMem: Temporal-Hierarchical Memory Consolidation for Long-Horizon Conversational Agents

arXiv:2601.02845v2 Announce Type: replace-cross Abstract: Long-horizon conversational agents have to manage ever-growing interaction histories that quickly exceed the finite context windows of large l

Towards single-shot coherent imaging via overlap-free ptychography

arXiv:2602.21361v3 Announce Type: replace-cross Abstract: Ptychographic imaging at synchrotron and XFEL sources requires dense overlapping scans, limiting throughput and increasing dose. Extending coh

Tutorials

Transformer Semantic Genetic Programming for d-dimensional Symbolic Regression Problems

arXiv:2511.09416v2 Announce Type: replace Abstract: Transformer Semantic Genetic Programming (TSGP) is a semantic search approach that uses a pre-trained transformer model as a variation operator to g

tutorialsarxiv-cs-lg

TRUST: A Framework for Decentralized AI Service v.0.1

arXiv:2604.27132v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) and Multi-Agent Systems (MAS) in high-stakes domains demand reliable verification, yet centralized approaches suffer four

Tutorials

UHR-Net: An Uncertainty-Aware Hypergraph Refinement Network for Medical Image Segmentation

arXiv:2604.28095v1 Announce Type: new Abstract: Accurate lesion segmentation is crucial for clinical diagnosis and treatment planning. However, lesions often resemble surrounding tissues and exhibit i

tutorialsarxiv-cs-cv

Vanishing Contributions: A Unified Framework for Smooth and Iterative Model Compression

arXiv:2510.09696v2 Announce Type: replace-cross Abstract: The increasing scale of Deep Neural Networks (DNNs) increases the need for compression techniques such as pruning, quantization, and low-rank

VeraRetouch: A Lightweight Fully Differentiable Framework for Multi-Task Reasoning Photo Retouching

arXiv:2604.27375v1 Announce Type: new Abstract: Reasoning photo retouching has gained significant traction, requiring models to analyze image defects, give reasoning processes, and execute precise ret

Visual Analysis of Multi-outcome Causal Graphs

model-releasesarxiv-cs-lg

arXiv:2408.02679v3 Announce Type: replace Abstract: We introduce a visual analysis method for multiple causal graphs with different outcome variables, namely, multi-outcome causal graphs. Multi-outcom

Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling

arXiv:2604.28185v1 Announce Type: new Abstract: Recent visual generation models have made major progress in photorealism, typography, instruction following, and interactive editing, yet they still str

Agents

When Agents Evolve, Institutions Follow

arXiv:2604.27691v1 Announce Type: new Abstract: Across millennia, complex societies have faced the same coordination problem of how to organize collective action among cognitively bounded and informat

agentsarxiv-cs-ai

When training Grok 4.3, we spoke directly with devs and businesses to understand what they actually needed: a model that’s fast, affordable,…

model-releaseselon-musk--x

When training Grok 4.3, we spoke directly with devs and businesses to understand what they actually needed: a model that’s fast, affordable, and great at tool calling. The result is a daily driver tha

WST-X Series: Wavelet Scattering Transform for Interpretable Speech Deepfake Detection

arXiv:2602.02980v2 Announce Type: replace-cross Abstract: In this work, we focus on front-end design for speech deepfake detectors, the component that determines the discriminative acoustic cues provi

ZAYAN: Disentangled Contrastive Transformer for Tabular Remote Sensing Data

arXiv:2604.27606v1 Announce Type: cross Abstract: Learning informative representations from tabular data in remote sensing and environmental science is challenging due to heterogeneity, scarce labels,

A Multistage Extraction Pipeline for Long Scanned Financial Documents: An Empirical Study in Industrial KYC Workflows

arXiv:2604.26462v1 Announce Type: new Abstract: Structured information extraction from long, multilingual scanned financial documents is a core requirement in industrial KYC and compliance workflows.

A Practice of Post-Training on Llama-3 70B with Optimal Selection of Additional Language Mixture Ratio

arXiv:2409.06624v4 Announce Type: replace-cross Abstract: Large Language Models (LLM) often need to be Continual Pre-Trained (CPT) to obtain unfamiliar language skills or adapt to new domains. The hug

A Priori Sampling of Transition States with Guided Diffusion

arXiv:2603.25980v2 Announce Type: replace-cross Abstract: Transition states, the first-order saddle points on the potential energy surfaces, govern the kinetics and mechanisms of chemical reactions an

researcharxiv-cs-lg

Hardware

A projection-based framework for gradient-free and parallel learning

arXiv:2506.05878v2 Announce Type: replace Abstract: We present a feasibility-seeking approach to neural network training. This mathematical optimization framework is distinct from conventional gradien

hardwarearxiv-cs-lg

A Scoping Review of LLM-as-a-Judge in Healthcare and the MedJUDGE Framework

arXiv:2604.25933v1 Announce Type: cross Abstract: As large language models (LLMs) increasingly generate and process clinical text, scalable evaluation has become critical. LLM-as-a-Judge (LaaJ), which

A Self-Calibrating Framework for Analog Circuit Sizing Using LLM-Derived Analytical Equations

arXiv:2604.07387v2 Announce Type: replace-cross Abstract: We present a design automation framework for analog circuit sizing that produces calibrated, topology-specific analytical equations from raw c

A Survey of Process Reward Models: From Outcome Signals to Process Supervisions for Large Language Models

arXiv:2510.08049v3 Announce Type: replace-cross Abstract: Although Large Language Models (LLMs) exhibit advanced reasoning ability, conventional alignment remains largely dominated by outcome reward m

A Survey on the Safety and Security Threats of Computer-Using Agents: JARVIS or Ultron?

arXiv:2505.10924v4 Announce Type: replace-cross Abstract: Recently, AI-driven interactions with computing devices have advanced from basic prototype tools to sophisticated, LLM-based systems that emul

Adaptive and Fine-grained Module-wise Expert Pruning for Efficient LoRA-MoE Fine-Tuning

model-releasesarxiv-cs-lg

arXiv:2604.26340v1 Announce Type: new Abstract: LoRA-MoE has emerged as an effective paradigm for parameter-efficient fine-tuning, combining the low training cost of LoRA with the increased adaptation

Anchored Confabulation: Partial Evidence Non-Monotonically Amplifies Confident Hallucination in LLMs

arXiv:2604.25931v1 Announce Type: new Abstract: We identify a previously unknown calibration property of large language models: providing one confirmed intermediate fact toward a multi-step reasoning

AnimateAnyMesh++: A Flexible 4D Foundation Model for High-Fidelity Text-Driven Mesh Animation

arXiv:2604.26917v1 Announce Type: new Abstract: Recent advances in 4D content generation have attracted increasing attention, yet creating high-quality animated 3D models remains challenging due to th

researcharxiv-cs-cv

Anthropic unveils BioMysteryBench to test Claude's bioinformatics skills against human experts, and says Mythos solved ~30% of 23 questions that stumped experts (Anthropic)

Anthropic: Anthropic unveils BioMysteryBench to test Claude's bioinformatics skills against human experts, and says Mythos solved ~30% of 23 questions that stumped experts — In this post, Brianna, a r

model-releasestechmeme

Associative-State Universal Transformers: Sparse Retrieval Meets Structured Recurrence

arXiv:2604.25930v1 Announce Type: new Abstract: We study whether a structured recurrent state can serve as a compact associative backbone for language modeling while still supporting exact retrieval.

Asynchronous Federated Unlearning with Invariance Calibration for Medical Imaging

arXiv:2604.26809v1 Announce Type: new Abstract: Federated Unlearning (FU) is an emerging paradigm in Federated Learning (FL) that enables participating clients to fully remove their contributions from

researcharxiv-cs-lg

Auditing Marketing Budget Allocation with Hindsight Regret

arXiv:2604.25977v1 Announce Type: cross Abstract: Organizations routinely make strategic budget allocations under operational constraints, but often lack a principled way to assess whether realized al

BioGraphletQA: Knowledge-Anchored Generation of Complex QA Datasets

arXiv:2604.26048v1 Announce Type: new Abstract: This paper presents a principled and scalable framework for systematically generating complex Question Answering (QA) data. In the core of this framewor

Bridge: Basis-Driven Causal Inference Marries VFMs for Domain Generalization

arXiv:2604.26820v1 Announce Type: new Abstract: Detectors often suffer from degraded performance, primarily due to the distributional gap between the source and target domains. This issue is especiall

CacheRAG: A Semantic Caching System for Retrieval-Augmented Generation in Knowledge Graph Question Answering

arXiv:2604.26176v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) has significantly advanced Knowledge Graph Question Answerin