Search: “framework”

Green Prompting: Characterizing Prompt-driven Energy Costs of LLM Inference

arXiv:2503.10666v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have become widely used across various domains spanning search engines, code generation, and text creation. Howev

Human

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Research

Grounding Before Generalizing: How AI Differs from Humans in Causal Transfer

DGX agent

arXiv:2604.24062v1 Announce Type: new Abstract: Extracting abstract causal structures and applying them to novel situations is a hallmark of human intelligence. While Large Language Models (LLMs) and

researcharxiv-cs-ai

28 Apr 2026

GSAR: Typed Grounding for Hallucination Detection and Recovery in Multi-Agent LLMs

arXiv:2604.23366v1 Announce Type: new Abstract: Autonomous multi-agent LLM systems are increasingly deployed to investigate operational incidents and produce structured diagnostic reports. Their trust

HardFlow: Hard-Constrained Sampling for Flow-Matching Models via Trajectory Optimization

arXiv:2511.08425v3 Announce Type: replace Abstract: Diffusion and flow-matching have emerged as powerful methodologies for generative modeling, with remarkable success in capturing complex data distri

Hierarchical Prototype-based Domain Priors for Multiple Instance Learning in Multimodal Histopathology Analysis

arXiv:2604.23982v1 Announce Type: new Abstract: Digital pathology has fundamentally altered diagnostic workflows by enabling the computational analysis of gigapixel Whole Slide Images (WSIs), yet effe

safetyarxiv-cs-cv

Hierarchical Spatio-Channel Clustering for Efficient Model Compression in Medical Image Analysis

model-releasesarxiv-cs-cv

arXiv:2604.23375v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) have become increasingly difficult to deploy in resource-constrained environments due to their large memory and com

Hybrid JIT-CUDA Graph Optimization for Low-Latency Large Language Model Inference

arXiv:2604.23467v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved strong performance across natural language and multimodal tasks, yet their practical deployment remains con

Implicit Humanization in Everyday LLM Moral Judgments

arXiv:2604.22764v1 Announce Type: cross Abstract: Recent adoption of conversational information systems has expanded the scope of user queries to include complex tasks such as personal advice-seeking.

INHerit-SG: Incremental Hierarchical Semantic Scene Graphs with RAG-Style Retrieval

model-releasesarxiv-cs-ro

arXiv:2602.12971v2 Announce Type: replace Abstract: Driven by recent advancements in foundation models, semantic scene graphs have emerged as a promising paradigm for high-level 3D environmental abstr

Tutorials

Investigating the Representation of Backchannels and Fillers in Fine-tuned Language Models

arXiv:2509.20237v2 Announce Type: replace Abstract: Backchannels and fillers are important linguistic expressions in dialogue, but often treated as 'noise' to be bypassed in modern transformer-based l

tutorialsarxiv-cs-cl

KERV: Kinematic-Rectified Speculative Decoding for Embodied VLA Models

arXiv:2603.01581v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models build a token-domain robot control paradigm, yet suffer from low speed. Speculative Decoding (SD) is an op

Hardware

Latent Inter-Frame Pruning: A Training-Free Method Bridging Traditional Video Compression and Modern Diffusion Transformers for Efficient Generation

arXiv:2604.23858v1 Announce Type: new Abstract: Video generation, while capable of generating realistic videos, is computationally expensive and slow, prohibiting real-time applications. In this paper

hardwarearxiv-cs-cv

Leveraging Human Feedback for Semantically-Relevant Skill Discovery

arXiv:2604.24127v1 Announce Type: cross Abstract: Unsupervised skill discovery in reinforcement learning aims to intrinsically motivate agents to discover diverse and useful behaviours. However, uncon

Leveraging Spatial Transcriptomics as Alternative to Manual Annotations for Deep Learning-Based Nuclei Analysis

arXiv:2604.23481v1 Announce Type: new Abstract: Deep learning-based nuclei segmentation and classification in pathology images typically rely on large-scale pixel-level manual annotations, which are c

LILogic Net: Compact Logic Gate Networks with Learnable Connectivity for Efficient Hardware Deployment

arXiv:2511.12340v2 Announce Type: replace Abstract: Efficient machine learning deployment requires models that account for hardware constraints. Because binary logic gates are the fundamental primitiv

LLMs Reading the Rhythms of Daily Life: Aligned Understanding for Behavior Prediction and Generation

arXiv:2604.23578v1 Announce Type: cross Abstract: Human daily behavior unfolds as complex sequences shaped by intentions, preferences, and context. Effectively modeling these behaviors is crucial for

Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation

arXiv:2603.17717v3 Announce Type: replace-cross Abstract: Supervised detection of network attacks has always been a critical part of network intrusion detection systems (NIDS). Nowadays, in a pivotal

Tutorials

MAE-Based Self-Supervised Pretraining for Data-Efficient Medical Image Segmentation Using nnFormer

arXiv:2604.22854v1 Announce Type: cross Abstract: Transformer architectures, including nnFormer,have demonstrated promising results in volumetric medical image segmentation by being able to capture lo

tutorialsarxiv-cs-ai

MEMCoder: Multi-dimensional Evolving Memory for Private-Library-Oriented Code Generation

arXiv:2604.24222v1 Announce Type: cross Abstract: Large Language Models (LLMs) excel at general code generation, but their performance drops sharply in enterprise settings that rely on internal privat

Meta-Aligner: Bidirectional Preference-Policy Optimization for Multi-Objective LLMs Alignment

arXiv:2604.24178v1 Announce Type: cross Abstract: Multi-Objective Alignment aims to align Large Language Models (LLMs) with diverse and often conflicting human values by optimizing multiple objectives

MetaGAI: A Large-Scale and High-Quality Benchmark for Generative AI Model and Data Card Generation

arXiv:2604.23539v1 Announce Type: new Abstract: The rapid proliferation of Generative AI necessitates rigorous documentation standards for transparency and governance. However, manual creation of Mode

Applications

Modular Sensory Stream for Integrating Physical Feedback in Vision-Language-Action Models

arXiv:2604.23272v1 Announce Type: new Abstract: Humans understand and interact with the real world by relying on diverse physical feedback beyond visual perception. Motivated by this, recent approache

applicationsarxiv-cs-ro

Multi-Plane HyperX: A Low-Latency and Cost-Effective Network for Large-Scale AI and HPC Systems

arXiv:2604.23519v1 Announce Type: cross Abstract: Multi-plane architectures have become increasingly prevalent in the Fat-Tree networks of AI data centers. By leveraging multiple ports on a single net

Multi-Scale Contrastive Learning for Video Temporal Grounding

arXiv:2412.07157v3 Announce Type: replace Abstract: Temporal grounding, which localizes video moments related to a natural language query, is a core problem of vision-language learning and video under

Multimodal QUD: Inquisitive Questions from Scientific Figures

arXiv:2604.23733v1 Announce Type: new Abstract: Asking inquisitive questions while reading, and looking for their answers, is an important part in human discourse comprehension, curiosity, and creativ

researcharxiv-cs-cl

Agents

NeoAMT: Neologism-Aware Agentic Machine Translation with Reinforcement Learning

arXiv:2601.03790v3 Announce Type: replace-cross Abstract: Neologism-aware machine translation aims to translate source sentences containing neologisms into target languages. This field remains underex

agentsarxiv-cs-ai

OAMVOS:2nd Report for 5th PVUW MOSE Track

arXiv:2604.22837v1 Announce Type: cross Abstract: SAM-based dense trackers provide strong short-term mask propagation but remain fragile under long occlusion, fast motion, viewpoint change, and distra

Omni-o3: Deep Nested Omnimodal Deduction for Deliberative Audio-Visual Reasoning

arXiv:2604.24191v1 Announce Type: new Abstract: Omnimodal understanding entails a massive, highly redundant search space of cross-modal interactions, demanding focused and deliberative reasoning. Curr

safetyarxiv-cs-cv

On the Complementarity of Quantum and Classical Features: Adaptive Hybrid Quantum-Classical Feature Fusion for Breast Cancer Classification

arXiv:2604.22903v1 Announce Type: cross Abstract: The integration of quantum machine learning with classical deep learning offers promising avenues for medical image analysis by mapping data into high

OpenPodcar2: a robust, ROS2 vehicle for self-driving research

arXiv:2604.24242v1 Announce Type: new Abstract: OpenPodcar2 is a robust, ROS2-interfaced, low-cost, open source hardware and software, autonomous vehicle platform based on an off-the-shelf, hard-canop

safetyarxiv-cs-ro

Otherness as a Quality in Designing Expressive Robotic Touch

arXiv:2604.23402v1 Announce Type: cross Abstract: Haptic technologies have advanced rapidly, yet exploration of robotic touch remains dominated by replicating realistic environmental cues or hand gest

researcharxiv-cs-ro

ParkingScenes: A Structured Dataset for End-to-End Autonomous Parking in Simulation Scenes

arXiv:2604.22835v1 Announce Type: cross Abstract: Autonomous parking remains a critical yet challenging task in intelligent driving systems, particularly within constrained urban environments where ma

Passage-Aware Structural Mapping for RGB-D Visual SLAM

arXiv:2604.24707v1 Announce Type: new Abstract: Doorways and passages are critical structural elements for indoor robot navigation, yet they remain underexplored in modern Visual SLAM (VSLAM) framewor

researcharxiv-cs-ro

Personalized Worked Example Generation from Student Code Submissions using Pattern-based Knowledge Components

arXiv:2604.24758v1 Announce Type: cross Abstract: Adaptive programming practice often relies on fixed libraries of worked examples and practice problems, which require substantial authoring effort and

PhysCodeBench: Benchmarking Physics-Aware Symbolic Simulation of 3D Scenes via Self-Corrective Multi-Agent Refinement

arXiv:2604.23580v1 Announce Type: cross Abstract: Physics-aware symbolic simulation of 3D scenes is critical for robotics, embodied AI, and scientific computing, requiring models to understand natural

Point Cloud Registration for Fusion between SPECT MPI and CTA Images

arXiv:2604.24524v1 Announce Type: new Abstract: Clinical fusion of Single Photon Emission Computed Tomography Myocardial Perfusion Imaging (SPECT MPI) and Computed Tomography Angiography (CTA) remains

Predicting Wind Loads on Container Ships in Harbor Environments through Multi-Fidelity Modeling

model-releasesarxiv-cs-lg

arXiv:2604.22882v1 Announce Type: new Abstract: Modern container ships face higher wind loads due to increased windage areas, making accurate predictions of wind loads essential for mooring design. Ex

Projected Attainable Speed Space: A Driving Efficiency Metric Connecting Instantaneous Evaluation to Travel Time

model-releasesarxiv-cs-ro

arXiv:2604.24295v1 Announce Type: new Abstract: Inefficient driving behaviors, such as overly conservative yielding, remain a key obstacle to deployment of autonomous vehicles (AVs). Instantaneous dri

Reclaiming Residual Knowledge: A Novel Paradigm to Low-Bit Quantization

arXiv:2408.00923v2 Announce Type: replace-cross Abstract: This paper explores a novel paradigm in low-bit (i.e. 4-bits or lower) quantization, differing from existing state-of-the-art methods, by fram

Scalable Production Scheduling: Linear Complexity via Unified Homogeneous Graphs

arXiv:2604.23841v1 Announce Type: cross Abstract: Efficiently solving the Job Shop Scheduling Problem in real-world industrial applications requires policies that are both computationally lean and top

SEARCH-R: Structured Entity-Aware Retrieval with Chain-of-Reasoning Navigator for Multi-hop Question Answering

arXiv:2604.24515v1 Announce Type: new Abstract: Multi-hop Question Answering (MHQA) aims to answer questions that require multi-step reasoning. It presents two key challenges: generating correct reaso

researcharxiv-cs-cl

See Further, Think Deeper: Advancing VLM's Reasoning Ability with Low-level Visual Cues and Reflection

arXiv:2604.24339v1 Announce Type: cross Abstract: Recent advances in Vision-Language Models (VLMs) have benefited from Reinforcement Learning (RL) for enhanced reasoning. However, existing methods sti

Self-Supervised Learning for Android Malware Detection on a Time-Stamped Dataset

arXiv:2604.23025v1 Announce Type: cross Abstract: Android malware detectors built with machine learning often suffer from temporal bias: models are trained and evaluated without respecting apps' actua

safetyarxiv-cs-lg

Semantic Segmentation for Histopathology using Learned Regularization based on Global Proportions

model-releasesarxiv-cs-cv

arXiv:2604.24347v1 Announce Type: cross Abstract: In pathology, the spatial distribution and proportions of tissue types are key indicators of disease progression, and are more readily available than

SemiSAM-O1: How far can we push the boundary of annotation-efficient medical image segmentation?

arXiv:2604.24109v1 Announce Type: new Abstract: Semi-supervised learning (SSL) has become a promising solution to alleviate the annotation burden of deep learning-based medical image segmentation mode

SEVerA: Verified Synthesis of Self-Evolving Agents

model-releasesarxiv-cs-lg

arXiv:2603.25111v2 Announce Type: replace Abstract: Recent advances have shown the effectiveness of self-evolving LLM agents on tasks such as program repair and scientific discovery. In this paradigm,

ShapeUP: Scalable Image-Conditioned 3D Editing

arXiv:2602.05676v2 Announce Type: replace Abstract: Recent advancements in 3D foundation models have enabled the generation of high-fidelity assets, yet precise 3D manipulation remains a significant c

Surface Sensitivity in Lean 4 Autoformalization

arXiv:2604.23135v1 Announce Type: new Abstract: Natural-language variation poses a key challenge in Lean autoformalization: semantically equivalent paraphrases of the same theorem statements can induc