Search: “benchmark”

ITS-Mina: A Harris Hawks Optimization-Based All-MLP Framework with Iterative Refinement and External Attention for Multivariate Time Series Forecasting

arXiv:2604.27981v1 Announce Type: cross Abstract: Multivariate time series forecasting plays a pivotal role in numerous real-world applications, including financial analysis, energy management, and tr

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JI-ADF: Joint-Individual Learning with Adaptive Decision Fusion for Multimodal Skin Lesion Classification

arXiv:2604.27343v1 Announce Type: new Abstract: Skin lesion classification is essential for early dermatological diagnosis, yet many existing computer-aided systems rely primarily on dermoscopic image

Judge, Then Drive: A Critic-Centric Vision Language Action Framework for Autonomous Driving

arXiv:2604.27366v1 Announce Type: new Abstract: Recent advances in vision language action (VLA) models have shown remarkable potential for autonomous driving by directly mapping multimodal inputs to c

LaST-R1: Reinforcing Action via Adaptive Physical Latent Reasoning for VLA Models

arXiv:2604.28192v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have increasingly incorporated reasoning mechanisms for complex robotic manipulation. However, existing approaches

Learning Rate Engineering: From Coarse Single Parameter to Layered Evolution

arXiv:2604.27295v1 Announce Type: new Abstract: Learning rate scheduling has evolved from the single global fixed rate of early SGD to sophisticated layer-wise adaptive strategies. We systematize this

LLMs as ASP Programmers: Self-Correction Enables Task-Agnostic Nonmonotonic Reasoning

arXiv:2604.27960v1 Announce Type: new Abstract: Recent large language models (LLMs) have achieved impressive reasoning milestones but continue to struggle with high computational costs, logical incons

LLMs Capture Emotion Labels, Not Emotion Uncertainty: Distributional Analysis and Calibration of Human--LLM Judgment Gaps

arXiv:2604.27345v1 Announce Type: new Abstract: Human annotators frequently disagree on emotion labels, yet most evaluations of Large Language Model (LLM) emotion annotation collapse these judgments i

researcharxiv-cs-cl

Lost in Space? Vision-Language Models Struggle with Relative Camera Pose Estimation

arXiv:2601.22228v2 Announce Type: replace-cross Abstract: We study whether vision-language models (VLMs) can solve relative camera pose estimation (RCPE) from image pairs, a direct test of multi-view

Low Rank Adaptation for Adversarial Perturbation

model-releasesarxiv-cs-lg

arXiv:2604.27487v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA), which leverages the insight that model updates typically reside in a low-dimensional space, has significantly improved the t

Math Education Digital Shadows for facilitating learning with LLMs: Math performance, anxiety and confidence in simulated students and AIs

arXiv:2604.27618v1 Announce Type: new Abstract: To enhance LLMs' impact on math education, we need data on their mathematical prowess and biases across prompts. To fill this gap, we introduce MEDS (Ma

MIFair: A Mutual-Information Framework for Intersectionality and Multiclass Fairness

arXiv:2604.28030v1 Announce Type: cross Abstract: Fairness in machine learning remains challenging due to its ethical complexity, the absence of a universal definition, and the need for context-specif

Mitigating Selection Bias in Large Language Models via Permutation-Aware GRPO

arXiv:2603.21016v2 Announce Type: replace-cross Abstract: Large language models (LLMs) used for multiple-choice and pairwise evaluation tasks often exhibit selection bias due to non-semantic factors l

MoCapAnything: Unified 3D Motion Capture for Arbitrary Skeletons from Monocular Videos

arXiv:2512.10881v2 Announce Type: replace Abstract: Motion capture now underpins content creation far beyond digital humans, yet most existing pipelines remain species- or template-specific. We formal

researcharxiv-cs-cv

Applications

Mull-Tokens: Modality-Agnostic Latent Thinking

arXiv:2512.10941v2 Announce Type: replace-cross Abstract: Reasoning goes beyond language; the real world requires reasoning about space, time, affordances, and much more that words alone cannot convey

applicationsarxiv-cs-ai

NanoKnow: How to Know What Your Language Model Knows

arXiv:2602.20122v2 Announce Type: replace-cross Abstract: How do large language models (LLMs) know what they know? Answering this question has been difficult because pre-training data is often a 'blac

NashPG: A Policy Gradient Method with Iteratively Refined Regularization for Finding Nash Equilibria

model-releasesarxiv-cs-lg

arXiv:2510.18183v2 Announce Type: replace Abstract: Finding Nash equilibria in two-player zero-sum imperfect-information games remains a central challenge in multi-agent reinforcement learning. Recent

NeocorRAG: Less Irrelevant Information, More Explicit Evidence, and More Effective Recall via Evidence Chains

arXiv:2604.27852v1 Announce Type: cross Abstract: Although precise recall is a core objective in Retrieval-Augmented Generation (RAG), a critical oversight persists in the field: improvements in retri

ObjectGraph: From Document Injection to Knowledge Traversal -- A Native File Format for the Agentic Era

arXiv:2604.27820v1 Announce Type: new Abstract: Every document format in existence was designed for a human reader moving linearly through text. Autonomous LLM agents do not read - they retrieve. This

Tutorials

Omni-Attribute: Open-vocabulary Attribute Encoder for Visual Concept Personalization

arXiv:2512.10955v2 Announce Type: replace Abstract: Visual concept personalization aims to transfer only specific image attributes, such as identity, expression, lighting, and style, into unseen conte

tutorialsarxiv-cs-cv

On the Expressive Power of GNNs to Solve Linear SDPs

arXiv:2604.27786v1 Announce Type: new Abstract: Semidefinite programs (SDPs) are a powerful framework for convex optimization and for constructing strong relaxations of hard combinatorial problems. Ho

researcharxiv-cs-lg

One Pass, Any Order: Position-Invariant Listwise Reranking for LLM-Based Recommendation

arXiv:2604.27599v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for recommendation reranking, but their listwise predictions can depend on the order in which candi

researcharxiv-cs-lg

OpenAI o1 System Card

arXiv:2412.16720v2 Announce Type: replace Abstract: The o1 model series is trained with large-scale reinforcement learning to reason using chain of thought. These advanced reasoning capabilities provi

OpenClassGen: A Large-Scale Corpus of Real-World Python Classes for LLM Research

arXiv:2504.15564v3 Announce Type: replace-cross Abstract: Existing class-level code generation datasets are either synthetic (ClassEval: 100 classes) or insufficient in scale for modern training needs

Optimization before Evaluation: Evaluation with Unoptimised Prompts Can be Misleading

arXiv:2604.27637v1 Announce Type: new Abstract: Current Large Language Model (LLM) evaluation frameworks utilize the same static prompt template across all models under evaluation. This differs from t

ORFS-agent: Tool-Using Agents for Chip Design Optimization

arXiv:2506.08332v3 Announce Type: replace Abstract: Machine learning has been widely used to optimize complex engineering workflows across numerous domains. In integrated circuit design, modern flows

Path-Lock Expert: Separating Reasoning Mode in Hybrid Thinking via Architecture-Level Separation

arXiv:2604.27201v1 Announce Type: cross Abstract: Hybrid-thinking language models expose explicit think and no-think modes, but current designs do not separate them cleanly. Even in no-think mode, mod

Perturbation Probing: A Two-Pass-per-Prompt Diagnostic for FFN Behavioral Circuits in Aligned LLMs

model-releasesarxiv-cs-cl

arXiv:2604.27401v1 Announce Type: new Abstract: Perturbation probing generates task-specific causal hypotheses for FFN neurons in large language models using two forward passes per prompt and no backp

PGOT: A Physics-Geometry Operator Transformer for Complex PDEs

arXiv:2512.23192v3 Announce Type: replace Abstract: While Transformers have demonstrated remarkable potential in modeling Partial Differential Equations (PDEs), modeling large-scale unstructured meshe

researcharxiv-cs-lg

PhotIQA: A photoacoustic image data set with image quality ratings

arXiv:2507.03478v2 Announce Type: replace-cross Abstract: Image quality assessment (IQA) is crucial in the evaluation stage of novel algorithms operating on images, including traditional and machine l

researcharxiv-cs-cv

PhyCo: Learning Controllable Physical Priors for Generative Motion

arXiv:2604.28169v1 Announce Type: cross Abstract: Modern video diffusion models excel at appearance synthesis but still struggle with physical consistency: objects drift, collisions lack realistic reb

PiCSAR: Probabilistic Confidence Selection And Ranking for Reasoning Chains

arXiv:2508.21787v2 Announce Type: replace-cross Abstract: Best-of-n sampling improves the accuracy of large language models (LLMs) and large reasoning models (LRMs) by generating multiple candidate so

Political Bias Audits of LLMs Capture Sycophancy to the Inferred Auditor

arXiv:2604.27633v1 Announce Type: new Abstract: Large language models (LLMs) are commonly evaluated for political bias based on their responses to fixed questionnaires, which typically place frontier

Post-Optimization Adaptive Rank Allocation for LoRA

arXiv:2604.27796v1 Announce Type: new Abstract: Exponential growth in the scale of modern foundation models has led to the widespread adoption of Low-Rank Adaptation (LoRA) as a parameter-efficient fi

PPA-Plan: Proactive Pitfall Avoidance for Reliable Planning in Long-Context LLM Reasoning

arXiv:2601.11908v2 Announce Type: replace Abstract: Large language models (LLMs) struggle with reasoning over long contexts where relevant information is sparsely distributed. Although plan-and-execut

researcharxiv-cs-cl

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

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

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

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

model-releasesarxiv-cs-cl

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

model-releasesarxiv-cs-cl

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