Search: “models”

Improving the Distributional Alignment of LLMs using Supervision

arXiv:2507.00439v4 Announce Type: replace Abstract: The ability to accurately align LLMs with diverse population groups on subjective questions would have great value. In this work, we show that addin

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Intentional Updates for Streaming Reinforcement Learning

DGX agent

arXiv:2604.19033v1 Announce Type: cross Abstract: In gradient-based learning, a step size chosen in parameter units does not produce a predictable per-step change in function output. This often leads

model-releasesarxiv-cs-ai

22 Apr 2026

Applications

Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors

arXiv:2604.19028v1 Announce Type: new Abstract: One of the most challenging problems in graph machine learning is generalizing across graphs with diverse properties. Graph neural networks (GNNs) face

applicationsarxiv-cs-lg

LiveVLN: Breaking the Stop-and-Go Loop in Vision-Language Navigation

model-releasesarxiv-cs-ro

arXiv:2604.19536v1 Announce Type: new Abstract: Recent navigation systems achieve strong benchmark results, yet real-world deployment often remains visibly stop-and-go. This bottleneck arises because

MedFlowSeg: Flow Matching for Medical Image Segmentation with Frequency-Aware Attention

arXiv:2604.19675v1 Announce Type: new Abstract: Flow matching has recently emerged as a principled framework for learning continuous-time transport maps, enabling efficient deterministic generation wi

researcharxiv-cs-cv

Multi-Cycle Spatio-Temporal Adaptation in Human-Robot Teaming

arXiv:2604.19670v1 Announce Type: cross Abstract: Effective human-robot teaming is crucial for the practical deployment of robots in human workspaces. However, optimizing joint human-robot plans remai

tutorialsarxiv-cs-ai

Multi-modal Reasoning with LLMs for Visual Semantic Arithmetic

arXiv:2604.19567v1 Announce Type: new Abstract: Reinforcement learning (RL) as post-training is crucial for enhancing the reasoning ability of large language models (LLMs) in coding and math. However,

safetyarxiv-cs-ai

Applications

Multi-view Crowd Tracking Transformer with View-Ground Interactions Under Large Real-World Scenes

arXiv:2604.19318v1 Announce Type: new Abstract: Multi-view crowd tracking estimates each person's tracking trajectories on the ground of the scene. Recent research works mainly rely on CNNs-based mult

applicationsarxiv-cs-cv

Local Ai

Ontology-Constrained Neural Reasoning in Enterprise Agentic Systems: A Neurosymbolic Architecture for Domain-Grounded AI Agents

arXiv:2604.00555v2 Announce Type: replace Abstract: Enterprise adoption of Large Language Models (LLMs) is constrained by hallucination, domain drift, and the inability to enforce regulatory complianc

local-aiarxiv-cs-ai

Paparazzo: Active Mapping of Moving 3D Objects

arXiv:2604.19556v1 Announce Type: new Abstract: Current 3D mapping pipelines generally assume static environments, which limits their ability to accurately capture and reconstruct moving objects. To a

PhysMem: Scaling Test-time Physical Memory for Robot Manipulation

arXiv:2602.20323v5 Announce Type: replace-cross Abstract: Reliable object manipulation requires understanding physical properties that vary across objects and environments. Vision-language model (VLM)

tutorialsarxiv-cs-ai

Policy Gradient Primal-Dual Method for Safe Reinforcement Learning from Human Feedback

arXiv:2604.19024v1 Announce Type: new Abstract: Safe Reinforcement Learning from Human Feedback (Safe RLHF) has recently achieved empirical success in developing helpful and harmless large language mo

safetyarxiv-cs-lg

RARE: Redundancy-Aware Retrieval Evaluation Framework for High-Similarity Corpora

arXiv:2604.19047v1 Announce Type: cross Abstract: Existing QA benchmarks typically assume distinct documents with minimal overlap, yet real-world retrieval-augmented generation (RAG) systems operate o

Realistic Handwritten Multi-Digit Writer (MDW) Number Recognition Challenges

arXiv:2512.00676v2 Announce Type: replace Abstract: Isolated digit classification has served as a motivating problem for decades of machine learning research. In real settings, numbers often occur as

Reasoning-Aware AIGC Detection via Alignment and Reinforcement

arXiv:2604.19172v1 Announce Type: new Abstract: The rapid advancement and widespread adoption of Large Language Models (LLMs) have elevated the need for reliable AI-generated content (AIGC) detection,

safetyarxiv-cs-ai

Resolving the Robustness-Precision Trade-off in Financial RAG through Hybrid Document-Routed Retrieval

arXiv:2603.26815v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) systems for financial document question answering typically follow a chunk-based paradigm: documents are

Revisiting Catastrophic Forgetting in Continual Knowledge Graph Embedding

arXiv:2604.19401v1 Announce Type: cross Abstract: Knowledge Graph Embeddings (KGEs) support a wide range of downstream tasks over Knowledge Graphs (KGs). In practice, KGs evolve as new entities and fa

researcharxiv-cs-ai

Revisiting RaBitQ and TurboQuant: A Symmetric Comparison of Methods, Theory, and Experiments

arXiv:2604.19528v1 Announce Type: cross Abstract: This technical note revisits the relationship between RaBitQ and TurboQuant under a unified comparison framework. We compare the two methods in terms

SAGE: Training-Free Semantic Evidence Composition for Edge-Cloud Inference under Hard Uplink Budgets

arXiv:2604.19623v1 Announce Type: cross Abstract: Edge-cloud hybrid inference offloads difficult inputs to a powerful remote model, but the uplink channel imposes hard per-request constraints on the n

researcharxiv-cs-cv

Sentipolis: Emotion-Aware Agents for Social Simulations

arXiv:2601.18027v2 Announce Type: replace Abstract: LLM agents are increasingly used for social simulation, yet emotion is often treated as a transient cue, causing emotional amnesia and weak long-hor

researcharxiv-cs-ai

Sherpa.ai Privacy-Preserving Multi-Party Entity Alignment without Intersection Disclosure for Noisy Identifiers

arXiv:2604.19219v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative model training among multiple parties without centralizing raw data. There are two main paradigms in FL:

safetyarxiv-cs-ai

SMART-Ship: A Comprehensive Synchronized Multi-modal Aligned Remote Sensing Targets Dataset and Benchmark for Berthed Ships Analysis

arXiv:2508.02384v2 Announce Type: replace Abstract: Given the limitations of satellite orbits and imaging conditions, multi-modal remote sensing (RS) data is crucial in enabling long-term earth observ

STAR-Teaming: A Strategy-Response Multiplex Network Approach to Automated LLM Red Teaming

arXiv:2604.18976v1 Announce Type: new Abstract: While Large Language Models (LLMs) are widely used, they remain susceptible to jailbreak prompts that can elicit harmful or inappropriate responses. Thi

safetyarxiv-cs-cl

StepFly: Agentic Troubleshooting Guide Automation for Incident Diagnosis

arXiv:2510.10074v2 Announce Type: replace Abstract: Effective incident management in large-scale IT systems relies on troubleshooting guides (TSGs), but their manual execution is slow and error-prone.

TabEmb: Joint Semantic-Structure Embedding for Table Annotation

arXiv:2604.18939v1 Announce Type: new Abstract: Table annotation is crucial for making web and enterprise tables usable in downstream NLP applications. Unlike textual data where learning semantically

tutorialsarxiv-cs-lg

TabXEval: Why this is a Bad Table? An eXhaustive Rubric for Table Evaluation

arXiv:2505.22176v3 Announce Type: replace Abstract: Evaluating tables qualitatively and quantitatively poses a significant challenge, as standard metrics often overlook subtle structural and content-l

Temp-R1: A Unified Autonomous Agent for Complex Temporal KGQA via Reverse Curriculum Reinforcement Learning

arXiv:2601.18296v2 Announce Type: replace-cross Abstract: Temporal Knowledge Graph Question Answering (TKGQA) is inherently challenging, as it requires sophisticated reasoning over dynamic facts with

The Essence of Balance for Self-Improving Agents in Vision-and-Language Navigation

arXiv:2604.19064v1 Announce Type: new Abstract: In vision-and-language navigation (VLN), self-improvement from policy-induced experience, using only standard VLN action supervision, critically depends

safetyarxiv-cs-cv

Thinking Before Matching: A Reinforcement Reasoning Paradigm Towards General Person Re-Identification

arXiv:2604.19218v1 Announce Type: new Abstract: Learning identity-discriminative representations with multi-scene generality has become a critical objective in person re-identification (ReID). However

tutorialsarxiv-cs-cv

Time-Scale Coupling Between States and Parameters in Recurrent Neural Networks

arXiv:2508.12121v5 Announce Type: replace Abstract: We show that gating mechanisms in recurrent neural networks (RNNs) induce lag-dependent and direction-dependent effective learning rates, even when

VideoAgent: Personalized Synthesis of Scientific Videos

arXiv:2509.11253v2 Announce Type: replace Abstract: The technical complexity of research papers often limits their reach, necessitating more accessible formats like scientific videos to disseminate ke

Voice of India: A Large-Scale Benchmark for Real-World Speech Recognition in India

arXiv:2604.19151v1 Announce Type: new Abstract: Existing Indic ASR benchmarks often use scripted, clean speech and leaderboard driven evaluation that encourages dataset specific overfitting. In additi

ZC-Swish: Stabilizing Deep BN-Free Networks for Edge and Micro-Batch Applications

arXiv:2604.19453v1 Announce Type: new Abstract: Batch Normalization (BN) is a cornerstone of deep learning, yet it fundamentally breaks down in micro-batch regimes (e.g., 3D medical imaging) and non-I

A Comparative Evaluation of Geometric Accuracy in NeRF and Gaussian Splatting

arXiv:2604.18205v1 Announce Type: new Abstract: Recent advances in neural rendering have introduced numerous 3D scene representations. Although standard computer vision metrics evaluate the visual qua

Agents

A Goal Without a Plan Is Just a Wish: Efficient and Effective Global Planner Training for Long-Horizon Agent Tasks

arXiv:2510.05608v2 Announce Type: replace Abstract: Agents based on large language models (LLMs) struggle with brainless trial-and-error and generating hallucinatory actions due to a lack of global pl

agentsarxiv-cs-cl

A High-Accuracy Optical Music Recognition Method Based on Bottleneck Residual Convolutions

arXiv:2604.16446v1 Announce Type: new Abstract: Optical Music Recognition (OMR) aims to convert printed or handwritten music score images into editable symbolic representations. This paper presents an

safetyarxiv-cs-cv

A Note on TurboQuant and the Earlier DRIVE/EDEN Line of Work

arXiv:2604.18555v1 Announce Type: new Abstract: This note clarifies the relationship between the recent TurboQuant work and the earlier DRIVE (NeurIPS 2021) and EDEN (ICML 2022) schemes. DRIVE is a 1-

A Quasi-Experimental Developer Study of Security Training in LLM-Assisted Web Application Development

arXiv:2604.17763v1 Announce Type: cross Abstract: This paper presents a controlled quasi-experimental developer study examining whether a layer-based security training package is associated with impro

safetyarxiv-cs-lg

A Real-World Grasping-in-Clutter Performance Evaluation Benchmark for Robotic Food Waste Sorting

model-releasesarxiv-cs-ro

arXiv:2602.18835v2 Announce Type: replace Abstract: Food waste management is critical for sustainability, yet inorganic contaminants hinder recycling potential. Robotic automation accelerates sorting

A Survey of Spatial Memory Representations for Efficient Robot Navigation

arXiv:2604.16482v1 Announce Type: new Abstract: As vision-based robots navigate larger environments, their spatial memory grows without bound, eventually exhausting computational resources, particular

Adversarial Arena: Crowdsourcing Data Generation through Interactive Competition

arXiv:2604.17803v1 Announce Type: cross Abstract: Post-training Large Language Models requires diverse, high-quality data which is rare and costly to obtain, especially in low resource domains and for

safetyarxiv-cs-lg

Adverse-to-the-eXtreme Panoptic Segmentation: URVIS 2026 Study and Benchmark

arXiv:2604.16984v1 Announce Type: new Abstract: This paper presents the report of the URVIS 2026 challenge on adverse-to-extreme panoptic segmentation. As the first challenge of its kind, it attracted

Align Documents to Questions: Question-Oriented Document Rewriting for Retrieval-Augmented Generation

arXiv:2604.17325v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) enhances the factuality of Large Language Models (LLMs) by incorporating retrieved documents and/or generated conte

safetyarxiv-cs-cl

Althea: Human-AI Collaboration for Fact-Checking and Critical Reasoning

arXiv:2602.11161v2 Announce Type: replace-cross Abstract: The web's information ecosystem demands fact-checking systems that are both scalable and epistemically trustworthy. Automated approaches offer

Automatic Slide Updating with User-Defined Dynamic Templates and Natural Language Instructions

arXiv:2604.17894v1 Announce Type: new Abstract: Presentation slides are a primary medium for data-driven reporting, yet keeping complex, analytics-style decks up to date remains labor-intensive. Exist

Back to Repair: A Minimal Denoising Network for Time Series Anomaly Detection

arXiv:2604.17388v1 Announce Type: new Abstract: We introduce JuRe (Just Repair), a minimal denoising network for time series anomaly detection that exposes a central finding: architectural complexity

Balance-Guided Sparse Identification of Multiscale Nonlinear PDEs with Small-coefficient Terms

arXiv:2604.18414v1 Announce Type: new Abstract: Data-driven discovery of governing equations has advanced significantly in recent years; however, existing methods often struggle in multiscale systems

researcharxiv-cs-lg

BasketHAR: A Multimodal Dataset for Human Activity Recognition and Sport Analysis in Basketball Training Scenarios

arXiv:2604.17065v1 Announce Type: new Abstract: Human Activity Recognition (HAR) involves the automatic identification of user activities and has gained significant research interest due to its broad