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arXiv:2604.25477v1 Announce Type: new Abstract: Recent image editing models have achieved strong visual fidelity but often struggle with tasks requiring complex reasoning. To investigate and enhance t

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DEGround: An Effective Baseline for Ego-centric 3D Visual Grounding with a Homogeneous Framework

DGX agent

arXiv:2506.05199v3 Announce Type: replace Abstract: A core task in embodied intelligence is ego-centric 3D visual grounding. Existing methods typically adopt two-stage, heterogeneous pipelines that pa

safetyarxiv-cs-cv

29 Apr 2026

Detecting Dental Landmarks from Intraoral 3D Scans: the 3DTeethLand challenge

arXiv:2512.08323v2 Announce Type: replace Abstract: Teeth landmark detection is a key task in modern orthodontics, supporting advanced diagnosis, personalized treatment planning, and effective monitor

DGLight: DQN-Guided GRPO Fine-Tuning of Large Language Models for Traffic Signal Control

arXiv:2604.25259v1 Announce Type: new Abstract: Traffic signal control (TSC) plays a central role in reducing congestion and maintaining urban mobility. This dissertation introduces DGLight, a critic-

safetyarxiv-cs-lg

DIAL: Decoupling Intent and Action via Latent World Modeling for End-to-End VLA

arXiv:2603.29844v2 Announce Type: replace-cross Abstract: The development of Vision-Language-Action (VLA) models has been significantly accelerated by pre-trained Vision-Language Models (VLMs). Howeve

DiffAdapt: Difficulty-Adaptive Reasoning for Token-Efficient LLM Inference

arXiv:2510.19669v4 Announce Type: replace Abstract: Recent reasoning Large Language Models (LLMs) demonstrate remarkable problem-solving abilities but often generate long thinking traces whose utility

DiRe-RAPIDS: Topology-faithful dimensionality reduction at scale

arXiv:2604.25209v1 Announce Type: new Abstract: Dimensionality reduction methods such as UMAP and t-SNE are central tools for visualising high-dimensional data, but their local-neighborhood objectives

DiscreteRTC: Discrete Diffusion Policies are Natural Asynchronous Executors

arXiv:2604.25050v1 Announce Type: new Abstract: Unlike chatbots, physical AI must act while the world keeps evolving. Therefore, the inter-chunk pause of synchronous executors are fatal for dynamic ta

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Diverse Image Priors for Black-box Data-free Knowledge Distillation

arXiv:2604.25794v1 Announce Type: cross Abstract: Knowledge distillation (KD) represents a vital mechanism to transfer expertise from complex teacher networks to efficient student models. However, in

researcharxiv-cs-cv

Doing More With Less: Revisiting the Effectiveness of LLM Pruning for Test-Time Scaling

arXiv:2604.25098v1 Announce Type: cross Abstract: While current Large Language Models (LLMs) exhibit remarkable reasoning capabilities through test-time compute scaling (TTS), their massive parameter

Dont Stop Early: Scalable Enterprise Deep Research with Controlled Information Flow and Evidence-Aware Termination

arXiv:2604.24978v1 Announce Type: new Abstract: Enterprise deep research often fails to produce decision-ready reports due to uneven information coverage, context explosion, and premature stopping. We

Local Ai

DouC: Dual-Branch CLIP for Training-Free Open-Vocabulary Segmentation

arXiv:2604.24997v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation requires assigning pixel-level semantic labels while supporting an open and unrestricted set of categories. Traini

local-aiarxiv-cs-cv

Local Ai

Dynamic Decision Learning: Test-Time Evolution for Abnormality Grounding in Rare Diseases

arXiv:2604.24972v1 Announce Type: new Abstract: Clinical abnormality grounding for rare diseases is often hindered by data scarcity, making supervised fine-tuning impractical and single-pass inference

local-aiarxiv-cs-cl

Egocentric Tactile and Proximity Sensors as Observation Priors for Humanoid Collision Avoidance

arXiv:2604.25554v1 Announce Type: cross Abstract: Collision-free motion is often aided by tactile and proximity sensors distributed on the body of the robot due to their resistance to occlusion as opp

Enhancing Financial Report Question-Answering: A Retrieval-Augmented Generation System with Reranking Analysis

arXiv:2603.16877v2 Announce Type: replace Abstract: Financial analysts face significant challenges extracting information from lengthy 10-K reports, which often exceed 100 pages. This paper presents a

ESICA: A Scalable Framework for Text-Guided 3D Medical Image Segmentation

arXiv:2604.24876v1 Announce Type: new Abstract: Text guided 3D medical image segmentation offers a flexible alternative to class based and spatial prompt based models by allowing users to specify regi

EvoTSC: Evolving Feature Learning Models for Time Series Classification via Genetic Programming

arXiv:2604.25499v1 Announce Type: new Abstract: Time series classification is an important analytical task across diverse domains. However, its practical application is often hindered by the scarcity

Explainable AI for Jet Tagging: A Comparative Study of GNNExplainer, GNNShap, and GradCAM for Jet Tagging in the Lund Jet Plane

arXiv:2604.25885v1 Announce Type: cross Abstract: Graph neural networks such as ParticleNet and transformer based networks on point clouds such as ParticleTransformer achieve state-of-the-art performa

researcharxiv-cs-lg

Exploring Reasoning Reward Model for Agents

arXiv:2601.22154v2 Announce Type: replace-cross Abstract: Agentic Reinforcement Learning (Agentic RL) has achieved notable success in enabling agents to perform complex reasoning and tool use. However

FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use Environments

arXiv:2604.25135v1 Announce Type: new Abstract: Large Language Models are being increasingly deployed as the decision-making core of autonomous agents capable of effecting change in external environme

FARM: Enhancing Molecular Representations with Functional Group Awareness

arXiv:2410.02082v4 Announce Type: replace Abstract: We introduce Functional Group-Aware Representations for Small Molecules (FARM), a novel foundation model designed to bridge the gap between SMILES,

Agents

From Soliloquy to Agora: Memory-Enhanced LLM Agents with Decentralized Debate for Optimization Modeling

arXiv:2604.25847v1 Announce Type: cross Abstract: Optimization modeling underpins real-world decision-making in logistics, manufacturing, energy, and public services, but reliably solving such problem

agentsarxiv-cs-lg

From Syntax to Emotion: A Mechanistic Analysis of Emotion Inference in LLMs

arXiv:2604.25866v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in emotionally sensitive human-AI applications, yet little is known about how emotion recognition is

G-Loss: Graph-Guided Fine-Tuning of Language Models

arXiv:2604.25853v1 Announce Type: new Abstract: Traditional loss functions, including cross-entropy, contrastive, triplet, and su pervised contrastive losses, used for fine-tuning pre-trained language

Generalizable Human Gaussian Splatting via Multi-view Semantic Consistency

arXiv:2604.25466v1 Announce Type: new Abstract: Recently, generalizable human Gaussian splatting from sparse-view inputs has been actively studied for the photorealistic human rendering. Most existing

GeoSearch: Augmenting Worldwide Geolocalization with Web-Scale Reverse Image Search and Image Matching

arXiv:2604.25390v1 Announce Type: cross Abstract: Worldwide image geolocalization, which aims to predict the GPS coordinates of any image on Earth, remains challenging due to global visual diversity.

researcharxiv-cs-cv

Golden RPG: Confidence-Adaptive Region-Aware Noise for Compositional Text-to-Image Generation

arXiv:2604.25314v1 Announce Type: new Abstract: Compositional text-to-image (T2I) generation requires a model to honour multiple sub-prompts that describe distinct image regions. Recent work shows tha

Applications

GramSR: Visual Feature Conditioning for Diffusion-Based Super-Resolution

arXiv:2604.25457v1 Announce Type: new Abstract: Despite recent advances, single-image super-resolution (SR) remains challenging, especially in real-world scenarios with complex degradations. Diffusion

applicationsarxiv-cs-cv

GraphPL: Leveraging GNN for Efficient and Robust Modalities Imputation in Patchwork Learning

arXiv:2604.25352v1 Announce Type: new Abstract: Current research on distributed multi-modal learning typically assumes that clients can access complete information across all modalities, which may not

Grothendieck Graph Neural Networks Framework: An Algebraic Platform for Crafting Topology-Aware GNNs

arXiv:2412.08835v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) are almost universally built on a single primitive: the neighborhood. Regardless of architectural variations, message p

researcharxiv-cs-lg

HANDFUL: Sequential Grasp-Conditioned Dexterous Manipulation with Resource Awareness

model-releasesarxiv-cs-ro

arXiv:2604.25126v1 Announce Type: new Abstract: Dexterous robot hands offer rich opportunities for multifunctional manipulation, where a robot must execute multiple skills in sequence while maintainin

Hidden States as Early Signals: Step-level Trace Evaluation and Pruning for Efficient Test-Time Scaling

arXiv:2601.09093v2 Announce Type: replace Abstract: Large Language Models (LLMs) can enhance reasoning capabilities through test-time scaling by generating multiple traces. However, the combination of

Hierarchical Reinforcement Learning for the Dynamic VNE with Alternatives Problem

arXiv:2512.05207v2 Announce Type: replace-cross Abstract: Virtual Network Embedding (VNE) is a key enabler of network slicing, yet most formulations assume that each Virtual Network Request (VNR) has

How RL Unlocks the Aha Moment in Geometric Interleaved Reasoning

arXiv:2603.01070v2 Announce Type: replace Abstract: Solving complex geometric problems inherently requires interleaved reasoning: a tight alternation between constructing diagrams and performing logic

safetyarxiv-cs-cl

HuM-Eval: A Coarse-to-Fine Framework for Human-Centric Video Evaluation

arXiv:2604.25361v1 Announce Type: new Abstract: Video generation models have developed rapidly in recent years, where generating natural human motion plays a pivotal role. However, accurately evaluati

Image Classification via Random Dilated Convolution with Multi-Branch Feature Extraction and Context Excitation

arXiv:2604.25188v1 Announce Type: new Abstract: Image classification remains a fundamental yet challenging task in computer vision, particularly when fine-grained feature extraction and background noi

Interactive Episodic Memory with User Feedback

arXiv:2604.24893v1 Announce Type: new Abstract: In episodic memory with natural language queries (EM-NLQ), a user may ask a question (e.g., 'Where did I place the mug?') that requires searching a long

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Interpretable Fuzzy Modeling Reveals Population-Level Representation Differences in P300 Brain Computer Interfaces Across Neurodivergent and Neurotypical Cohorts

arXiv:2604.24765v1 Announce Type: cross Abstract: P300-based brain-computer interfaces (BCIs) are widely used for communication, but population heterogeneity may alter the neural patterns available fo

jina-embeddings-v5-text: Task-Targeted Embedding Distillation

arXiv:2602.15547v2 Announce Type: replace Abstract: Text embedding models are widely used for semantic similarity tasks, including information retrieval, clustering, and classification. General-purpos

Large Language Models Explore by Latent Distilling

arXiv:2604.24927v1 Announce Type: new Abstract: Generating diverse responses is crucial for test-time scaling of large language models (LLMs), yet standard stochastic sampling mostly yields surface-le

Learning from Medical Entity Trees: An Entity-Centric Medical Data Engineering Framework for MLLMs

arXiv:2604.25296v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown transformative potential in medical applications, yet their performance is hindered by conventional

safetyarxiv-cs-cl

Less Is More: Fast and Accurate Reasoning with Cross-Head Unified Sparse Attention

arXiv:2508.07101v2 Announce Type: replace Abstract: Large reasoning models achieve strong performance through test-time scaling, but this incurs substantial computational overhead due to long decoding

Liquid Neural Network Models for Natural Gas Spot Price Time-Series Forecasting

arXiv:2604.24788v1 Announce Type: new Abstract: Natural gas is undoubtedly an essential component of the global energy system. Accurate short-term forecasting of natural gas price is challenging due t

LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation

arXiv:2604.25665v1 Announce Type: new Abstract: Reliable evaluation of large language model (LLM)-generated summaries remains an open challenge, particularly across heterogeneous domains and document

LongSumEval: Question-Answering Based Evaluation and Feedback-Driven Refinement for Long Document Summarization

arXiv:2604.25130v1 Announce Type: new Abstract: Evaluating long document summaries remains the primary bottleneck in summarization research. Existing metrics correlate weakly with human judgments and

Marco-MoE: Open Multilingual Mixture-of-Expert Language Models with Efficient Upcycling

arXiv:2604.25578v1 Announce Type: new Abstract: We present Marco-MoE, a suite of fully open multilingual sparse Mixture-of-Experts (MoE) models. Marco-MoE features a highly sparse design in which only

MGTEVAL: An Interactive Platform for Systemtic Evaluation of Machine-Generated Text Detectors

arXiv:2604.25152v1 Announce Type: cross Abstract: We present MGTEVAL, an extensible platform for systematic evaluation of Machine-Generated Text (MGT) detectors. Despite rapid progress in MGT detectio

MICo-150K: A Comprehensive Dataset Advancing Multi-Image Composition

arXiv:2512.07348v2 Announce Type: replace Abstract: In controllable image generation, synthesizing coherent and consistent images from multiple reference inputs, i.e., Multi-Image Composition (MICo),