Search: “benchmark”

Primus: Enforcing Attention Usage for 3D Medical Image Segmentation

arXiv:2503.01835v2 Announce Type: replace Abstract: Transformers have achieved remarkable success across multiple fields, yet their impact on 3D medical image segmentation remains limited with convolu

researcharxiv-cs-cv

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PRISM: Pre-alignment via Black-box On-policy Distillation for Multimodal Reinforcement Learning

DGX agent

arXiv:2604.28123v1 Announce Type: cross Abstract: The standard post-training recipe for large multimodal models (LMMs) applies supervised fine-tuning (SFT) on curated demonstrations followed by reinfo

model-releasesarxiv-cs-ai

1 May 2026

Progressive Multi-Agent Reasoning for Biological Perturbation Prediction

arXiv:2602.07408v2 Announce Type: replace Abstract: Predicting gene regulation responses to biological perturbations requires reasoning about underlying biological causalities. While large language mo

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

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

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

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

researcharxiv-cs-cl

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

researcharxiv-cs-cl

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