Search: “evaluation”

From UAV Imagery to Agronomic Reasoning: A Multimodal LLM Benchmark for Plant Phenotyping

arXiv:2604.09907v1 Announce Type: cross Abstract: To improve crop genetics, high-throughput, effective and comprehensive phenotyping is a critical prerequisite. While such tasks were traditionally per

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FS-DFM: Fast and Accurate Long Text Generation with Few-Step Diffusion Language Models

DGX agent

arXiv:2509.20624v5 Announce Type: replace-cross Abstract: Autoregressive language models (ARMs) deliver strong likelihoods, but are inherently serial: they generate one token per forward pass, which l

model-releasesarxiv-cs-ai

14 Apr 2026

Fusion Complexity Inversion: Why Simpler Cross View Modules Outperform SSMs and Cross View Attention Transformers for Pasture Biomass Regression

model-releasesarxiv-cs-cv

arXiv:2603.07819v3 Announce Type: replace Abstract: Accurate estimation of pasture biomass from agricultural imagery is critical for sustainable livestock management, yet existing methods are limited

Local Ai

Gait Recognition with Temporal Kolmogorov-Arnold Networks

arXiv:2604.09990v1 Announce Type: new Abstract: Gait recognition is a biometric modality that identifies individuals from their characteristic walking patterns. Unlike conventional biometric traits, g

local-aiarxiv-cs-cv

GaNI: Global and Near Field Illumination Aware Neural Inverse Rendering

arXiv:2403.15651v5 Announce Type: replace Abstract: In this paper, we present GaNI, a Global and Near-field Illumination-aware neural inverse rendering technique that can reconstruct geometry, albedo,

researcharxiv-cs-cv

GanitLLM: Difficulty-Aware Bengali Mathematical Reasoning through Curriculum-GRPO

arXiv:2601.06767v2 Announce Type: replace-cross Abstract: We present a Bengali mathematical reasoning model called GanitLLM (named after the Bangla word for mathematics, 'Ganit'), together with a new

researcharxiv-cs-ai

General-purpose LLMs as Models of Human Driver Behavior: The Case of Simplified Merging

arXiv:2604.09609v1 Announce Type: new Abstract: Human behavior models are essential as behavior references and for simulating human agents in virtual safety assessment of automated vehicles (AVs), yet

General365: Benchmarking General Reasoning in Large Language Models Across Diverse and Challenging Tasks

arXiv:2604.11778v1 Announce Type: cross Abstract: Contemporary large language models (LLMs) have demonstrated remarkable reasoning capabilities, particularly in specialized domains like mathematics an

Generalizable Deepfake Detection Based on Forgery-aware Layer Masking and Multi-artifact Subspace Decomposition

model-releasesarxiv-cs-cv

arXiv:2601.01041v3 Announce Type: replace Abstract: Deepfake detection remains highly challenging, particularly in cross-dataset scenarios and complex real-world settings. This challenge mainly arises

Generating High Quality Synthetic Data for Dutch Medical Conversations

arXiv:2604.09645v1 Announce Type: cross Abstract: Medical conversations offer insights into clinical communication often absent from Electronic Health Records. However, developing reliable clinical Na

researcharxiv-cs-ai

Generation-Augmented Generation: A Plug-and-Play Framework for Private Knowledge Injection in Large Language Models

arXiv:2601.08209v3 Announce Type: replace Abstract: In domains such as materials science, biomedicine, and finance, high-stakes deployment of large language models (LLMs) requires injecting private, d

Hardware

Generative Design for Direct-to-Chip Liquid Cooling for Data Centers

arXiv:2604.10941v1 Announce Type: cross Abstract: Rapid growth in artificial intelligence (AI) workloads is driving up data center power densities, increasing the need for advanced thermal management.

hardwarearxiv-cs-lg

Safety

GenProve: Learning to Generate Text with Fine-Grained Provenance

arXiv:2601.04932v2 Announce Type: replace Abstract: Large language models (LLM) often hallucinate, and while adding citations is a common solution, it is frequently insufficient for accountability as

safetyarxiv-cs-cl

GenTac: Generative Modeling and Forecasting of Soccer Tactics

arXiv:2604.11786v1 Announce Type: new Abstract: Modeling open-play soccer tactics is a formidable challenge due to the stochastic, multi-agent nature of the game. Existing computational approaches typ

Local Ai

Global monitoring of methane point sources using deep learning on hyperspectral radiance measurements from EMIT

arXiv:2604.10094v1 Announce Type: new Abstract: Anthropogenic methane (CH4) point sources drive near-term climate forcing, safety hazards, and system inefficiencies. Space-based imaging spectroscopy i

local-aiarxiv-cs-cv

GoT-R1: Unleashing Reasoning Capability of MLLM for Visual Generation with Reinforcement Learning

arXiv:2505.17022v2 Announce Type: replace-cross Abstract: Visual generation models have made remarkable progress in creating realistic images from text prompts, yet struggle with complex prompts that

Hardware

GPU-Accelerated Continuous-Time Successive Convexification for Contact-Implicit Legged Locomotion

arXiv:2604.09993v1 Announce Type: new Abstract: Contact-implicit trajectory optimization (CITO) enables the automatic discovery of contact sequences, but most methods rely on fine time discretization

hardwarearxiv-cs-ro

Hardening x402: PII-Safe Agentic Payments via Pre-Execution Metadata Filtering

arXiv:2604.11430v1 Announce Type: cross Abstract: AI agents that pay for resources via the x402 protocol embed payment metadata - resource URLs, descriptions, and reason strings - in every HTTP paymen

agentsarxiv-cs-ai

Head-wise Modality Specialization within MLLMs for Robust Fake News Detection under Missing Modality

arXiv:2604.09711v1 Announce Type: cross Abstract: Multimodal fake news detection (MFND) aims to verify news credibility by jointly exploiting textual and visual evidence. However, real-world news diss

applicationsarxiv-cs-cl

HeceTokenizer: A Syllable-Based Tokenization Approach for Turkish Retrieval

arXiv:2604.10665v1 Announce Type: new Abstract: HeceTokenizer is a syllable-based tokenizer for Turkish that exploits the deterministic six-pattern phonological structure of the language to construct

Help Without Being Asked: A Deployed Proactive Agent System for On-Call Support with Continuous Self-Improvement

arXiv:2604.09579v1 Announce Type: new Abstract: In large-scale cloud service platforms, thousands of customer tickets are generated daily and are typically handled through on-call dialogues. This high

agentsarxiv-cs-ai

Tutorials

Hierarchical Textual Knowledge for Enhanced Image Clustering

arXiv:2604.11144v1 Announce Type: cross Abstract: Image clustering aims to group images in an unsupervised fashion. Traditional methods focus on knowledge from visual space, making it difficult to dis

tutorialsarxiv-cs-cl

HiPRAG: Hierarchical Process Rewards for Efficient Agentic Retrieval Augmented Generation

arXiv:2510.07794v2 Announce Type: replace-cross Abstract: Agentic RAG is a powerful technique for incorporating external information that LLMs lack, enabling better problem solving and question answer

Tutorials

How to Bridge the Sim-to-Real Gap in Digital Twin-Aided Telecommunication Networks

arXiv:2507.07067v3 Announce Type: replace-cross Abstract: Training effective artificial intelligence models for telecommunications is challenging due to the scarcity of deployment-specific data. Real

tutorialsarxiv-cs-lg

How You Ask Matters! Adaptive RAG Robustness to Query Variations

arXiv:2604.10745v1 Announce Type: new Abstract: Adaptive Retrieval-Augmented Generation (RAG) promises accuracy and efficiency by dynamically triggering retrieval only when needed and is widely used i

Hunt Globally: Wide Search AI Agents for Drug Asset Scouting in Investing, Business Development, and Competitive Intelligence

arXiv:2602.15019v3 Announce Type: replace Abstract: Bio-pharmaceutical innovation has shifted: many new drug assets now originate outside the United States and are disclosed primarily via regional, no

IMPACT: A Dataset for Multi-Granularity Human Procedural Action Understanding in Industrial Assembly

arXiv:2604.10409v1 Announce Type: cross Abstract: We introduce IMPACT, a synchronized five-view RGB-D dataset for deployment-oriented industrial procedural understanding, built around real assembly an

Improving Layout Representation Learning Across Inconsistently Annotated Datasets via Agentic Harmonization

arXiv:2604.11042v1 Announce Type: new Abstract: Fine-tuning object detection (OD) models on combined datasets assumes annotation compatibility, yet datasets often encode conflicting spatial definition

agentsarxiv-cs-cv

Improving Pediatric Emergency Department Triage with Modality Dropout in Late Fusion Multimodal EHR Models

arXiv:2604.09905v1 Announce Type: new Abstract: Emergency department triage relies heavily on both quantitative vital signs and qualitative clinical notes, yet multimodal machine learning models predi

researcharxiv-cs-lg

In-situ process monitoring for defect detection in wire-arc additive manufacturing: an agentic AI approach

arXiv:2604.09889v1 Announce Type: new Abstract: AI agents are being increasingly deployed across a wide range of real-world applications. In this paper, we propose an agentic AI framework for in-situ

agentsarxiv-cs-ai

Inferring Dynamic Physical Properties from Video Foundation Models

arXiv:2510.02311v2 Announce Type: replace Abstract: We study the task of predicting dynamic physical properties from videos. More specifically, we consider physical properties that require temporal in

applicationsarxiv-cs-cv

Inferring World Belief States in Dynamic Real-World Environments

arXiv:2604.11020v1 Announce Type: new Abstract: We investigate estimating a human's world belief state using a robot's observations in a dynamic, 3D, and partially observable environment. The methods

applicationsarxiv-cs-ro

Infusing Theory of Mind into Socially Intelligent LLM Agents

arXiv:2509.22887v2 Announce Type: replace Abstract: Theory of Mind (ToM)-an understanding of the mental states of others-is a key aspect of human social intelligence, yet, chatbots and LLM-based socia

Integrating SAINT with Tree-Based Models: A Case Study in Employee Attrition Prediction

arXiv:2604.10337v1 Announce Type: new Abstract: Employee attrition presents a major challenge for organizations, increasing costs and reducing productivity. Predicting attrition accurately enables pro

applicationsarxiv-cs-lg

Integrating Semi-Supervised and Active Learning for Semantic Segmentation

arXiv:2501.19227v2 Announce Type: replace-cross Abstract: In this paper, we propose a novel active learning approach integrated with an improved semi-supervised learning framework to reduce the cost o

Interactive Interface For Semantic Segmentation Dataset Synthesis

arXiv:2506.23470v2 Announce Type: replace Abstract: The rapid advancement of AI and computer vision has significantly increased the demand for high-quality annotated datasets, particularly for semanti

applicationsarxiv-cs-cv

Safety

Interactive Learning for LLM Reasoning

arXiv:2509.26306v4 Announce Type: replace Abstract: Existing multi-agent learning approaches have developed interactive training environments to explicitly promote collaboration among multiple Large L

safetyarxiv-cs-ai

Is There Knowledge Left to Extract? Evidence of Fragility in Medically Fine-Tuned Vision-Language Models

arXiv:2604.09841v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly adapted through domain-specific fine-tuning, yet it remains unclear whether this improves reasoning bey

K-Way Energy Probes for Metacognition Reduce to Softmax in Discriminative Predictive Coding Networks

arXiv:2604.11011v1 Announce Type: cross Abstract: We present this as a negative result with an explanatory mechanism, not as a formal upper bound. Predictive coding networks (PCNs) admit a K-way energ

Knowledge Integration in Differentiable Models: A Comparative Study of Data-Driven, Soft-Constrained, and Hard-Constrained Paradigms for Identification and Control of the Single Machine Infinite Bus System

model-releasesarxiv-cs-lg

arXiv:2602.09667v2 Announce Type: replace Abstract: Integrating domain knowledge into neural networks is a central challenge in scientific machine learning. Three paradigms have emerged -- data-driven

LABBench2: An Improved Benchmark for AI Systems Performing Biology Research

arXiv:2604.09554v1 Announce Type: new Abstract: Optimism for accelerating scientific discovery with AI continues to grow. Current applications of AI in scientific research range from training dedicate

LangFlow: Continuous Diffusion Rivals Discrete in Language Modeling

arXiv:2604.11748v1 Announce Type: new Abstract: Continuous diffusion models have achieved strong performance across domains such as images. However, in language modeling, prior continuous diffusion la

researcharxiv-cs-cl

Tutorials

Language Reconstruction with Brain Predictive Coding from fMRI Data

arXiv:2405.11597v2 Announce Type: replace-cross Abstract: Many recent studies have shown that the perception of speech can be decoded from brain signals and subsequently reconstructed as continuous la

tutorialsarxiv-cs-ai

Learnable Motion-Focused Tokenization for Effective and Efficient Video Unsupervised Domain Adaptation

arXiv:2604.09955v1 Announce Type: new Abstract: Video Unsupervised Domain Adaptation (VUDA) poses a significant challenge in action recognition, requiring the adaptation of a model from a labeled sour

applicationsarxiv-cs-cv

Safety

Learning from Emptiness: De-biasing Listwise Rerankers with Content-Agnostic Probability Calibration

arXiv:2604.10150v1 Announce Type: new Abstract: Generative listwise reranking leverages global context for superior retrieval but is plagued by intrinsic position bias, where models exhibit structural

safetyarxiv-cs-ai

Local Ai

Learning Hierarchical and Geometry-Aware Graph Representations for Text-to-CAD

arXiv:2604.10075v1 Announce Type: new Abstract: Text-to-CAD code generation is a long-horizon task that translates textual instructions into long sequences of interdependent operations. Existing metho

local-aiarxiv-cs-ai

Learning Preference-Based Objectives from Clinical Narratives for Sequential Treatment Decision-Making

arXiv:2604.10783v1 Announce Type: new Abstract: Designing reward functions remains a central challenge in reinforcement learning (RL) for healthcare, where outcomes are sparse, delayed, and difficult

applicationsarxiv-cs-ai

Learning Robustness at Test-Time from a Non-Robust Teacher

model-releasesarxiv-cs-cv

arXiv:2604.11590v1 Announce Type: new Abstract: Nowadays, pretrained models are increasingly used as general-purpose backbones and adapted at test-time to downstream environments where target data are