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Do VLMs Truly 'Read' Candlesticks? A Multi-Scale Benchmark for Visual Stock Price Forecasting

arXiv:2604.12659v1 Announce Type: cross Abstract: Vision-language models(VLMs) are increasingly applied to visual stock price forecasting, yet existing benchmarks inadequately evaluate their understan

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Model Releases

Don't Show Pixels, Show Cues: Unlocking Visual Tool Reasoning in Language Models via Perception Programs

DGX agent

arXiv:2604.12896v1 Announce Type: new Abstract: Multimodal language models (MLLMs) are increasingly paired with vision tools (e.g., depth, flow, correspondence) to enhance visual reasoning. However, d

model-releasesarxiv-cs-cv

15 Apr 2026

DoseRAD2026 Challenge dataset: AI accelerated photon and proton dose calculation for radiotherapy

arXiv:2604.12778v1 Announce Type: cross Abstract: Purpose: Accurate dose calculation is essential in radiotherapy for precise tumor irradiation while sparing healthy tissue. With the growing adoption

DPC-VQA: Decoupling Quality Perception and Residual Calibration for Video Quality Assessment

arXiv:2604.12813v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) have shown promising performance on video quality assessment (VQA) tasks. However, adapting them to new

Drawing on Memory: Dual-Trace Encoding Improves Cross-Session Recall in LLM Agents

arXiv:2604.12948v1 Announce Type: new Abstract: LLM agents with persistent memory store information as flat factual records, providing little context for temporal reasoning, change tracking, or cross-

Dreamer-CDP: Improving Reconstruction-free World Models Via Continuous Deterministic Representation Prediction

arXiv:2603.07083v2 Announce Type: replace Abstract: Model-based reinforcement learning (MBRL) agents operating in high-dimensional observation spaces, such as Dreamer, rely on learning abstract repres

Dress-ED: Instruction-Guided Editing for Virtual Try-On and Try-Off

arXiv:2603.22607v2 Announce Type: replace Abstract: Recent advances in Virtual Try-On (VTON) and Virtual Try-Off (VTOFF) have greatly improved photo-realistic fashion synthesis and garment reconstruct

Dual-Modality Anchor-Guided Filtering for Test-time Prompt Tuning

arXiv:2604.12403v1 Announce Type: new Abstract: Test-Time Prompt Tuning (TPT) adapts vision-language models using augmented views, but its effectiveness is hindered by the challenge of determining whi

EDGE-Shield: Efficient Denoising-staGE Shield for Violative Content Filtering via Scalable Reference-Based Matching

arXiv:2604.06063v2 Announce Type: replace Abstract: The advent of Text-to-Image generative models poses significant risks of copyright violation and deepfake generation. Since the rapid proliferation

EEG-Based Multimodal Learning via Hyperbolic Mixture-of-Curvature Experts

arXiv:2604.12579v1 Announce Type: new Abstract: Electroencephalography (EEG)-based multimodal learning integrates brain signals with complementary modalities to improve mental state assessment, provid

Efficient Adversarial Training via Criticality-Aware Fine-Tuning

arXiv:2604.12780v1 Announce Type: cross Abstract: Vision Transformer (ViT) models have achieved remarkable performance across various vision tasks, with scalability being a key advantage when applied

EgoEsportsQA: An Egocentric Video Benchmark for Perception and Reasoning in Esports

arXiv:2604.12320v1 Announce Type: cross Abstract: While video large language models (Video-LLMs) excel in understanding slow-paced, real-world egocentric videos, their capabilities in high-velocity, i

ELoG-GS: Dual-Branch Gaussian Splatting with Luminance-Guided Enhancement for Extreme Low-light 3D Reconstruction

arXiv:2604.12592v1 Announce Type: new Abstract: This paper presents our approach to the NTIRE 2026 3D Restoration and Reconstruction Challenge (Track 1), which focuses on reconstructing high-quality 3

Empirical Evaluation of PDF Parsing and Chunking for Financial Question Answering with RAG

arXiv:2604.12047v1 Announce Type: new Abstract: PDF files are primarily intended for human reading rather than automated processing. In addition, the heterogeneous content of PDFs, such as text, table

Evaluating Differential Privacy Against Membership Inference in Federated Learning: Insights from the NIST Genomics Red Team Challenge

arXiv:2604.12737v1 Announce Type: cross Abstract: While Federated Learning (FL) mitigates direct data exposure, the resulting trained models remain susceptible to membership inference attacks (MIAs).

Evaluating LLM-Generated ACSL Annotations for Formal Verification

arXiv:2602.13851v3 Announce Type: replace-cross Abstract: Formal specifications are crucial for building verifiable and dependable software systems, yet generating accurate and verifiable specificatio

Evaluating Relational Reasoning in LLMs with REL

arXiv:2604.12176v1 Announce Type: new Abstract: Relational reasoning is the ability to infer relations that jointly bind multiple entities, attributes, or variables. This ability is central to scienti

FABLE: Fine-grained Fact Anchoring for Unstructured Model Editing

arXiv:2604.12559v1 Announce Type: new Abstract: Unstructured model editing aims to update models with real-world text, yet existing methods often memorize text holistically without reliable fine-grain

FaCT: Faithful Concept Traces for Explaining Neural Network Decisions

arXiv:2510.25512v2 Announce Type: replace-cross Abstract: Deep networks have shown remarkable performance across a wide range of tasks, yet getting a global concept-level understanding of how they fun

Fast and principled equation discovery from chaos to climate

arXiv:2604.11929v1 Announce Type: new Abstract: Our ability to predict, control, and ultimately understand complex systems rests on discovering the equations that govern their dynamics. Identifying th

FAST-DIPS: Adjoint-Free Analytic Steps and Hard-Constrained Likelihood Correction for Diffusion-Prior Inverse Problems

arXiv:2603.01591v2 Announce Type: replace-cross Abstract: Training-free diffusion priors enable inverse-problem solvers without retraining, but for nonlinear forward operators data consistency often r

FeaXDrive: Feasibility-aware Trajectory-Centric Diffusion Planning for End-to-End Autonomous Driving

arXiv:2604.12656v1 Announce Type: cross Abstract: End-to-end diffusion planning has shown strong potential for autonomous driving, but the physical feasibility of generated trajectories remains insuff

Filtered Reasoning Score: Evaluating Reasoning Quality on a Model's Most-Confident Traces

arXiv:2604.11996v1 Announce Type: cross Abstract: Should we trust Large Language Models (LLMs) with high accuracy? LLMs achieve high accuracy on reasoning benchmarks, but correctness alone does not re

Fine-tuning Factor Augmented Neural Lasso for Heterogeneous Environments

arXiv:2604.12288v1 Announce Type: cross Abstract: Fine-tuning is a widely used strategy for adapting pre-trained models to new tasks, yet its methodology and theoretical properties in high-dimensional

FlowBoost Reveals Phase Transitions and Spectral Structure in Finite Free Information Inequalities

arXiv:2604.11922v1 Announce Type: cross Abstract: Using FlowBoost, a closed-loop deep generative optimization framework for extremal structure discovery, we investigate ell^p-generalizations of the fi

Fragile Preferences: A Deep Dive Into Order Effects in Large Language Models

arXiv:2506.14092v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in decision-support systems for high-stakes domains such as hiring and university admissions,

From Imitation to Discrimination: Progressive Curriculum Learning for Robust Web Navigation

arXiv:2604.12666v1 Announce Type: cross Abstract: Text-based web agents offer computational efficiency for autonomous web navigation, yet developing robust agents remains challenging due to the noisy

From Plan to Action: How Well Do Agents Follow the Plan?

arXiv:2604.12147v1 Announce Type: cross Abstract: Agents aspire to eliminate the need for task-specific prompt crafting through autonomous reason-act-observe loops. Still, they are commonly instructed

Frontier-Eng: Benchmarking Self-Evolving Agents on Real-World Engineering Tasks with Generative Optimization

arXiv:2604.12290v1 Announce Type: new Abstract: Current LLM agent benchmarks, which predominantly focus on binary pass/fail tasks such as code generation or search-based question answering, often negl

FRTSearch: Unified Detection and Parameter Inference of Fast Radio Transients using Instance Segmentation

arXiv:2604.12344v1 Announce Type: cross Abstract: The exponential growth of data from modern radio telescopes presents a significant challenge to traditional single-pulse search algorithms, which are

Fully Homomorphic Encryption on Llama 3 model for privacy preserving LLM inference

arXiv:2604.12168v1 Announce Type: cross Abstract: The applications of Generative Artificial Intelligence (GenAI) and their intersections with data-driven fields, such as healthcare, finance, transport

Fundus Image-based Glaucoma Screening via Retinal Knowledge-Oriented Dynamic Multi-Level Feature Integration

arXiv:2604.12351v1 Announce Type: new Abstract: Automated diagnosis based on color fundus photography is essential for large-scale glaucoma screening. However, existing deep learning models are typica

GCA Framework: A Gulf-Grounded Dataset and Agentic Pipeline for Climate Decision Support

arXiv:2604.12306v1 Announce Type: cross Abstract: Climate decision-making in the Gulf increasingly demands systems that can translate heterogeneous scientific and policy evidence into actionable guida

GeM-EA: A Generative and Meta-learning Enhanced Evolutionary Algorithm for Streaming Data-Driven Optimization

arXiv:2604.12336v1 Announce Type: cross Abstract: Streaming Data-Driven Optimization (SDDO) problems arise in many applications where data arrive continuously and the optimization environment evolves

Generative Anonymization in Event Streams

arXiv:2604.12803v1 Announce Type: new Abstract: Neuromorphic vision sensors offer low latency and high dynamic range, but their deployment in public spaces raises severe data protection concerns. Rece

Generative Refinement Networks for Visual Synthesis

arXiv:2604.13030v1 Announce Type: new Abstract: While diffusion models dominate the field of visual generation, they are computationally inefficient, applying a uniform computational effort regardless

GF-Score: Certified Class-Conditional Robustness Evaluation with Fairness Guarantees

arXiv:2604.12757v1 Announce Type: cross Abstract: Adversarial robustness is essential for deploying neural networks in safety-critical applications, yet standard evaluation methods either require expe

Global optimization tailored for graphics processing units: Complete and rigorous search for large-scale nonlinear minimization

arXiv:2507.01770v4 Announce Type: replace-cross Abstract: This paper introduces a numerical method to enclose the global minimum of a nonlinear function subject to simple bounds on the variables. Usin

GlotOCR Bench: OCR Models Still Struggle Beyond a Handful of Unicode Scripts

arXiv:2604.12978v1 Announce Type: new Abstract: Optical character recognition (OCR) has advanced rapidly with the rise of vision-language models, yet evaluation has remained concentrated on a small cl

GoodPoint: Learning Constructive Scientific Paper Feedback from Author Responses

arXiv:2604.11924v1 Announce Type: new Abstract: While LLMs hold significant potential to transform scientific research, we advocate for their use to augment and empower researchers rather than to auto

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling

arXiv:2511.05477v2 Announce Type: replace Abstract: Medical image segmentation demands models that achieve high accuracy while maintaining computational efficiency and clinical interpretability. While

Growing Pains: Extensible and Efficient LLM Benchmarking Via Fixed Parameter Calibration

arXiv:2604.12843v1 Announce Type: new Abstract: The rapid release of both language models and benchmarks makes it increasingly costly to evaluate every model on every dataset. In practice, models are

GTCN-G: A Residual Graph-Temporal Fusion Network for Imbalanced Intrusion Detection

arXiv:2510.07285v3 Announce Type: replace-cross Abstract: The escalating complexity of network threats and the inherent class imbalance in traffic data present formidable challenges for modern Intrusi

GTPBD-MM: A Global Terraced Parcel and Boundary Dataset with Multi-Modality

arXiv:2604.12315v1 Announce Type: new Abstract: Agricultural parcel extraction plays an important role in remote sensing-based agricultural monitoring, supporting parcel surveying, precision managemen

Hard Negative Sample-Augmented DPO Post-Training for Small Language Models

arXiv:2512.19728v2 Announce Type: replace Abstract: Large language models (LLMs) continue to struggle with mathematical reasoning, and common post-training pipelines often reduce each generated soluti

HazardArena: Evaluating Semantic Safety in Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2604.12447v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models inherit rich world knowledge from vision-language backbones and acquire executable skills via action demonstrations.

How memory can affect collective and cooperative behaviors in an LLM-Based Social Particle Swarm

arXiv:2604.12250v1 Announce Type: new Abstract: This study examines how model-specific characteristics of Large Language Model (LLM) agents, including internal alignment, shape the effect of memory on

HSG-12M: A Large-Scale Benchmark of Spatial Multigraphs from the Energy Spectra of Non-Hermitian Crystals

arXiv:2506.08618v4 Announce Type: replace-cross Abstract: AI is transforming scientific research by revealing new ways to understand complex physical systems, but its impact remains constrained by the