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arXiv:2604.08916v1 Announce Type: new Abstract: Conventional 3D instance segmentation methods rely on labor-intensive 3D annotations for supervised training, which limits their scalability and general

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Natural Riemannian gradient for learning functional tensor networks

DGX agent

arXiv:2604.09263v1 Announce Type: cross Abstract: We consider machine learning tasks with low-rank functional tree tensor networks (TTN) as the learning model. While in the case of least-squares regre

model-releasesarxiv-cs-lg

13 Apr 2026

Neighbourhood Transformer: Switchable Attention for Monophily-Aware Graph Learning

arXiv:2604.08980v1 Announce Type: cross Abstract: Graph neural networks (GNNs) have been widely adopted in engineering applications such as social network analysis, chemical research and computer visi

applicationsarxiv-cs-ai

Nested Radially Monotone Polar Occupancy Estimation: Clinically-Grounded Optic Disc and Cup Segmentation for Glaucoma Screening

arXiv:2604.09062v1 Announce Type: new Abstract: Valid segmentation of the optic disc (OD) and optic cup (OC) from fundus photographs is essential for glaucoma screening. Unfortunately, existing deep l

researcharxiv-cs-cv

Neurons Speak in Ranges: Breaking Free from Discrete Neuronal Attribution

arXiv:2502.06809v3 Announce Type: replace-cross Abstract: Pervasive polysemanticity in large language models (LLMs) undermines discrete neuron-concept attribution, posing a significant challenge for m

local-aiarxiv-cs-ai

NOMAD: Generating Embeddings for Massive Distributed Graphs

arXiv:2604.09419v1 Announce Type: new Abstract: Successful machine learning on graphs or networks requires embeddings that not only represent nodes and edges as low-dimensional vectors but also preser

applicationsarxiv-cs-lg

Off-the-shelf Vision Models Benefit Image Manipulation Localization

arXiv:2604.09096v1 Announce Type: new Abstract: Image manipulation localization (IML) and general vision tasks are typically treated as two separate research directions due to the fundamental differen

local-aiarxiv-cs-cv

On Semiotic-Grounded Interpretive Evaluation of Generative Art

arXiv:2604.08641v1 Announce Type: cross Abstract: Interpretation is essential to deciphering the language of art: audiences communicate with artists by recovering meaning from visual artifacts. Howeve

Online Quantile Regression for Nonparametric Additive Models

arXiv:2604.08969v1 Announce Type: cross Abstract: This paper introduces a projected functional gradient descent algorithm (P-FGD) for training nonparametric additive quantile regression models in onli

researcharxiv-cs-lg

Plasticity-Enhanced Multi-Agent Mixture of Experts for Dynamic Objective Adaptation in UAVs-Assisted Emergency Communication Networks

arXiv:2604.09028v1 Announce Type: cross Abstract: Unmanned aerial vehicles serving as aerial base stations can rapidly restore connectivity after disasters, yet abrupt changes in user mobility and tra

safetyarxiv-cs-lg

Post-Selection Distributional Model Evaluation

arXiv:2603.23055v2 Announce Type: replace-cross Abstract: Formal model evaluation methods typically certify that a model satisfies a prescribed target key performance indicator (KPI) level. However, i

safetyarxiv-cs-lg

Precise Shield: Explaining and Aligning VLLM Safety via Neuron-Level Guidance

arXiv:2604.08881v1 Announce Type: new Abstract: In real-world deployments, Vision-Language Large Models (VLLMs) face critical challenges from multilingual and multimodal composite attacks: harmful ima

Prototype-Regularized Federated Learning for Cross-Domain Aspect Sentiment Triplet Extraction

arXiv:2604.09123v1 Announce Type: new Abstract: Aspect Sentiment Triplet Extraction (ASTE) aims to extract all sentiment triplets of aspect terms, opinion terms, and sentiment polarities from a senten

researcharxiv-cs-cl

Provable Post-Training Quantization: Theoretical Analysis of OPTQ and Qronos

arXiv:2508.04853v2 Announce Type: replace-cross Abstract: Post-training quantization (PTQ) has become a crucial tool for reducing the memory and compute costs of modern deep neural networks, including

RAM: Recover Any 3D Human Motion in-the-Wild

arXiv:2603.19929v2 Announce Type: replace-cross Abstract: RAM incorporates a motion-aware semantic tracker with adaptive Kalman filtering to achieve robust identity association under severe occlusions

researcharxiv-cs-ai

Region-Constrained Group Relative Policy Optimization for Flow-Based Image Editing

arXiv:2604.09386v1 Announce Type: new Abstract: Instruction-guided image editing requires balancing target modification with non-target preservation. Recently, flow-based models have emerged as a stro

safetyarxiv-cs-cv

ReplicatorBench: Benchmarking LLM Agents for Replicability in Social and Behavioral Sciences

arXiv:2602.11354v2 Announce Type: replace Abstract: The literature has witnessed an emerging interest in AI agents for automated assessment of scientific papers. Existing benchmarks focus primarily on

Revisiting Image Manipulation Localization under Realistic Manipulation Scenarios

arXiv:2509.20006v3 Announce Type: replace Abstract: With the large models easing the labor-intensive manipulation process, image manipulations in today's real scenarios often entail a complex manipula

Robust Adaptive Backstepping Impedance Control of Robots in Unknown Environments

arXiv:2604.09323v1 Announce Type: new Abstract: This paper presents a Robust Adaptive Backstepping Impedance Control (RABIC) strategy for robots operating in contact-rich and uncertain environments. T

researcharxiv-cs-ro

SAGE: A Service Agent Graph-guided Evaluation Benchmark

arXiv:2604.09285v1 Announce Type: new Abstract: The development of Large Language Models (LLMs) has catalyzed automation in customer service, yet benchmarking their performance remains challenging. Ex

SEA-Eval: A Benchmark for Evaluating Self-Evolving Agents Beyond Episodic Assessment

arXiv:2604.08988v1 Announce Type: new Abstract: Current LLM-based agents demonstrate strong performance in episodic task execution but remain constrained by static toolsets and episodic amnesia, faili

Agents

Self-Sovereign Agent

arXiv:2604.08551v1 Announce Type: cross Abstract: We investigate the emerging prospect of self-sovereign agents -- AI systems that can economically sustain and extend their own operation without human

agentsarxiv-cs-lg

Self-Supervised Slice-to-Volume Reconstruction with Gaussian Representations for Fetal MRI

arXiv:2601.22990v2 Announce Type: replace-cross Abstract: Reconstructing 3D fetal MR volumes from motion-corrupted stacks of 2D slices is a crucial and challenging task. Conventional slice-to-volume r

researcharxiv-cs-ai

Semantic Intent Fragmentation: A Single-Shot Compositional Attack on Multi-Agent AI Pipelines

arXiv:2604.08608v1 Announce Type: cross Abstract: We introduce Semantic Intent Fragmentation (SIF), an attack class against LLM orchestration systems where a single, legitimately phrased request cause

SessionIntentBench: A Multi-task Inter-session Intention-shift Modeling Benchmark for E-commerce Customer Behavior Understanding

model-releasesarxiv-cs-cl

arXiv:2507.20185v2 Announce Type: replace Abstract: Session history is a common way of recording user interacting behaviors throughout a browsing activity with multiple products. For example, if an us

{sf TriDeliver}: Cooperative Air-Ground Instant Delivery with UAVs, Couriers, and Crowdsourced Ground Vehicles

arXiv:2604.09049v1 Announce Type: new Abstract: Instant delivery, shipping items before critical deadlines, is essential in daily life. While multiple delivery agents, such as couriers, Unmanned Aeria

applicationsarxiv-cs-ro

SHIFT: Steering Hidden Intermediates in Flow Transformers

arXiv:2604.09213v1 Announce Type: new Abstract: Diffusion models have become leading approaches for high-fidelity image generation. Recent DiT-based diffusion models, in particular, achieve strong pro

safetyarxiv-cs-cv

SimScale: Learning to Drive via Real-World Simulation at Scale

arXiv:2511.23369v3 Announce Type: replace Abstract: Achieving fully autonomous driving systems requires learning rational decisions in a wide span of scenarios, including safety-critical and out-of-di

Skill-Conditioned Visual Geolocation for Vision-Language

arXiv:2604.09025v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown a promising ability in image geolocation, but they still lack structured geographic reasoning and the capacit

Agents

SkillForge: Forging Domain-Specific, Self-Evolving Agent Skills in Cloud Technical Support

arXiv:2604.08618v1 Announce Type: cross Abstract: Deploying LLM-powered agents in enterprise scenarios such as cloud technical support demands high-quality, domain-specific skills. However, existing s

agentsarxiv-cs-ai

SPPO: Sequence-Level PPO for Long-Horizon Reasoning Tasks

arXiv:2604.08865v1 Announce Type: new Abstract: Proximal Policy Optimization (PPO) is central to aligning Large Language Models (LLMs) in reasoning tasks with verifiable rewards. However, standard tok

STCast: Adaptive Boundary Alignment for Global and Regional Weather Forecasting

arXiv:2509.25210v3 Announce Type: replace-cross Abstract: To gain finer regional forecasts, many works have explored the regional integration from the global atmosphere, e.g., by solving boundary equa

StreamMeCo: Long-Term Agent Memory Compression for Efficient Streaming Video Understanding

arXiv:2604.09000v1 Announce Type: new Abstract: Vision agent memory has shown remarkable effectiveness in streaming video understanding. However, storing such memory for videos incurs substantial memo

Strips as Tokens: Artist Mesh Generation with Native UV Segmentation

arXiv:2604.09132v1 Announce Type: new Abstract: Recent advancements in autoregressive transformers have demonstrated remarkable potential for generating artist-quality meshes. However, the token order

researcharxiv-cs-cv

StructRL: Recovering Dynamic Programming Structure from Learning Dynamics in Distributional Reinforcement Learning

arXiv:2604.08620v1 Announce Type: cross Abstract: Reinforcement learning is typically treated as a uniform, data-driven optimization process, where updates are guided by rewards and temporal-differenc

Structured Exploration and Exploitation of Label Functions for Automated Data Annotation

arXiv:2604.08578v1 Announce Type: cross Abstract: High-quality labeled data is critical for training reliable machine learning and deep learning models, yet manual annotation remains costly and error-

researcharxiv-cs-ai

Structured Uncertainty guided Clarification for LLM Agents

arXiv:2511.08798v2 Announce Type: replace-cross Abstract: LLM agents with tool-calling capabilities often fail when user instructions are ambiguous or incomplete, leading to incorrect invocations and

Tango: Taming Visual Signals for Efficient Video Large Language Models

arXiv:2604.09547v1 Announce Type: new Abstract: Token pruning has emerged as a mainstream approach for developing efficient Video Large Language Models (Video LLMs). This work revisits and advances th

local-aiarxiv-cs-cv

Task-Aware Bimanual Affordance Prediction via VLM-Guided Semantic-Geometric Reasoning

arXiv:2604.08726v1 Announce Type: new Abstract: Bimanual manipulation requires reasoning about where to interact with an object and which arm should perform each action, a joint affordance localizatio

local-aiarxiv-cs-ro

The causal relation between off-street parking and electric vehicle adoption in Scotland

arXiv:2604.09271v1 Announce Type: new Abstract: The transition to electric mobility hinges on maximising aggregate adoption while also facilitating equitable access. This study examines whether the 'c

safetyarxiv-cs-lg

The Impact of Gait Pattern Personalization on the Perception of Rigid Robotic Guidance: A Pilot User Experience Evaluation

arXiv:2512.17425v2 Announce Type: replace Abstract: Exoskeletons modulate human movement across diverse applications, from performance augmentation to daily-life assistance. These systems often enforc

researcharxiv-cs-ro

Agents

The new @LangChain podcast is all about empowerment

LangChain has launched a new podcast focused on the theme of empowerment, as announced by Harrison Chase on X (formerly Twitter). The podcast likely features discussions around AI development, buildin

agentsharrison-chase--x

The nextAI Solution to the NeurIPS 2023 LLM Efficiency Challenge

model-releasesarxiv-cs-lg

arXiv:2604.09034v1 Announce Type: new Abstract: The rapid evolution of Large Language Models (LLMs) has significantly impacted the field of natural language processing, but their growing complexity ra

Think Less, Know More: State-Aware Reasoning Compression with Knowledge Guidance for Efficient Reasoning

arXiv:2604.09150v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) achieve strong performance on complex tasks by leveraging long Chain-of-Thought (CoT), but often suffer from overthinking,

safetyarxiv-cs-cl

Thinking about trying Ollama Pro — how does it compare to Claude/Codex?

This Reddit thread from r/ollama discusses user perspectives on **Ollama Pro** as a paid/upgraded tier compared to cloud-based AI coding assistants like Anthropic's Claude and OpenAI's Codex, likely f

model-releasesr-ollama

Tiled Prompts: Overcoming Prompt Misguidance in Image and Video Super-Resolution

arXiv:2602.03342v2 Announce Type: replace-cross Abstract: Text-conditioned diffusion models have advanced image and video super-resolution by using prompts as semantic priors, and modern super-resolut

applicationsarxiv-cs-ai

TopoFlow: Topography-aware Pollutant Flow Learning for High-Resolution Air Quality Prediction

arXiv:2602.16821v2 Announce Type: replace Abstract: We propose TopoFlow (Topography-aware pollutant Flow learning), a physics-guided neural network for efficient, high-resolution air quality predictio

researcharxiv-cs-lg

Tora3: Trajectory-Guided Audio-Video Generation with Physical Coherence

arXiv:2604.09057v1 Announce Type: new Abstract: Audio-video (AV) generation has recently made strong progress in perceptual quality and multimodal coherence, yet generating content with plausible moti

safetyarxiv-cs-cv