Search: “models”

STS-Mixer: Spatio-Temporal-Spectral Mixer for 4D Point Cloud Video Understanding

arXiv:2604.11637v1 Announce Type: new Abstract: 4D point cloud videos capture rich spatial and temporal dynamics of scenes which possess unique values in various 4D understanding tasks. However, most

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TacMan-Turbo: Proactive Tactile Control for Robust and Efficient Articulated Object Manipulation

DGX agent

arXiv:2508.02204v4 Announce Type: replace Abstract: Adept manipulation of articulated objects is essential for robots to operate successfully in human environments. Such manipulation requires both eff

tutorialsarxiv-cs-ro

14 Apr 2026

Test-time Scaling over Perception: Resolving the Grounding Paradox in Thinking with Images

arXiv:2604.11025v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) have begun to support Thinking with Images by invoking visual tools such as zooming and cropping during

Text-Guided 6D Object Pose Rearrangement via Closed-Loop VLM Agents

arXiv:2604.09781v1 Announce Type: new Abstract: Vision-Language Models (VLMs) exhibit strong visual reasoning capabilities, yet they still struggle with 3D understanding. In particular, VLMs often fai

agentsarxiv-cs-cv

Local Ai

The Impact of Federated Learning on Distributed Remote Sensing Archives

arXiv:2604.11562v1 Announce Type: new Abstract: Remote sensing archives are inherently distributed: Earth observation missions such as Sentinel-1, Sentinel-2, and Sentinel-3 have collectively accumula

local-aiarxiv-cs-cv

The role of memorization and knowledge is to cache & reuse past cognitive work. It should be leveraged as a way to speed up cognition, not a…

researchfrancois-chollet--x

Francois Chollet argues that memorization and knowledge function as a cache for previously completed cognitive work, allowing it to be reused efficiently rather than recomputed. The purpose of storing

Applications

The Second Challenge on Real-World Face Restoration at NTIRE 2026: Methods and Results

arXiv:2604.10532v1 Announce Type: new Abstract: This paper provides a review of the NTIRE 2026 challenge on real-world face restoration, highlighting the proposed solutions and the resulting outcomes.

applicationsarxiv-cs-cv

The user interface of the future is your voice: Inside 8×8’s AI Studio

For years, the promise of “no-code” artificial intelligence has felt a bit like a “some assembly required” IKEA desk — sure, you aren’t sawing the wood yourself, but you’re trying to decipher how to a

tutorialssiliconangle

The Wasserstein transform

arXiv:1810.07793v2 Announce Type: replace Abstract: We introduce the Wasserstein Transform (WT), a general unsupervised framework for updating distance structures on given data sets with the purpose o

TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance

arXiv:2509.26627v2 Announce Type: replace Abstract: Designing dense rewards is crucial for reinforcement learning (RL), yet in robotics it often demands extensive manual effort and lacks scalability.

tutorialsarxiv-cs-ai

Topology-Aware PAC-Bayesian Generalization Analysis for Graph Neural Networks

arXiv:2604.10553v1 Announce Type: new Abstract: Graph neural networks have demonstrated excellent applicability to a wide range of domains, including social networks, biological systems, recommendatio

Towards an Appropriate Level of Reliance on AI: A Preliminary Reliance-Control Framework for AI in Software Engineering

arXiv:2604.10530v1 Announce Type: cross Abstract: How software developers interact with Artificial Intelligence (AI)-powered tools, including Large Language Models (LLMs), plays a vital role in how th

TRACE: An Experiential Framework for Coherent Multi-hop Knowledge Graph Question Answering

arXiv:2604.11193v1 Announce Type: new Abstract: Multi-hop Knowledge Graph Question Answering (KGQA) requires coherent reasoning across relational paths, yet existing methods often treat each reasoning

tutorialsarxiv-cs-cl

Uncertainty-Guided Attention and Entropy-Weighted Loss for Precise Plant Seedling Segmentation

arXiv:2604.10823v1 Announce Type: new Abstract: Plant seedling segmentation supports automated phenotyping in precision agriculture. Standard segmentation models face difficulties due to intricate bac

Utilizing and Calibrating Hindsight Process Rewards via Reinforcement with Mutual Information Self-Evaluation

arXiv:2604.11611v1 Announce Type: new Abstract: To overcome the sparse reward challenge in reinforcement learning (RL) for agents based on large language models (LLMs), we propose Mutual Information S

safetyarxiv-cs-cl

VERTIGO: Visual Preference Optimization for Cinematic Camera Trajectory Generation

arXiv:2604.02467v2 Announce Type: replace-cross Abstract: Cinematic camera control relies on a tight feedback loop between director and cinematographer, where camera motion and framing are continuousl

VideoStir: Understanding Long Videos via Spatio-Temporally Structured and Intent-Aware RAG

arXiv:2604.05418v2 Announce Type: replace-cross Abstract: Scaling multimodal large language models (MLLMs) to long videos is constrained by limited context windows. While retrieval-augmented generatio

Visual Enhanced Depth Scaling for Multimodal Latent Reasoning

arXiv:2604.10500v1 Announce Type: new Abstract: Multimodal latent reasoning has emerged as a promising paradigm that replaces explicit Chain-of-Thought (CoT) decoding with implicit feature propagation

safetyarxiv-cs-cv

What I’ve been building: ATOM Report, post-training course, finishing my book, and ongoing research

The author provided an update on several ongoing technical projects, including the ATOM Report, a new post-training course, and

tutorialsinterconnects

What's going on?

This Reddit post from r/ChatGPT, titled 'What's going on?', likely reflects user reactions and discussion around a notable change or issue with ChatGPT — such as the removal of specific models, unexpe

industryr-chatgpt

When Valid Signals Fail: Regime Boundaries Between LLM Features and RL Trading Policies

arXiv:2604.10996v1 Announce Type: cross Abstract: Can large language models (LLMs) generate continuous numerical features that improve reinforcement learning (RL) trading agents? We build a modular pi

A Semi-Automated Framework for 3D Reconstruction of Medieval Manuscript Miniatures

arXiv:2604.08610v1 Announce Type: new Abstract: This paper presents a semi-automated framework for transforming two-dimensional miniatures from medieval manuscripts into three-dimensional digital mode

Local Ai

Active Learning for Generalizable Detonation Performance Prediction of Energetic Materials

arXiv:2604.08744v1 Announce Type: cross Abstract: The discovery of new energetic materials is critical for advancing technologies from defense to private industry. However, experimental approaches rem

local-aiarxiv-cs-lg

ActivityEditor: Learning to Synthesize Physically Valid Human Mobility

arXiv:2604.05529v2 Announce Type: replace Abstract: Human mobility modeling is indispensable for diverse urban applications. However, existing data-driven methods often suffer from data scarcity, limi

Adaptive Dual Residual U-Net with Attention Gate and Multiscale Spatial Attention Mechanisms (ADRUwAMS)

arXiv:2604.08893v1 Announce Type: cross Abstract: Glioma is a harmful brain tumor that requires early detection to ensure better health results. Early detection of this tumor is key for effective trea

AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Society

arXiv:2502.08691v2 Announce Type: replace-cross Abstract: Understanding human behavior and society is a central focus in social sciences, with the rise of generative social science marking a significa

Automatic Self-supervised Learning for Social Recommendations

arXiv:2412.18735v3 Announce Type: replace-cross Abstract: In recent years, researchers have leveraged social relations to enhance recommendation performance. However, most existing social recommendati

tutorialsarxiv-cs-lg

B-MoE: A Body-Part-Aware Mixture-of-Experts 'All Parts Matter' Approach to Micro-Action Recognition

arXiv:2603.24245v3 Announce Type: replace Abstract: Micro-actions, fleeting and low-amplitude motions, such as glances, nods, or minor posture shifts, carry rich social meaning but remain difficult fo

Bandwidth-constrained Variational Message Encoding for Cooperative Multi-agent Reinforcement Learning

arXiv:2512.11179v3 Announce Type: replace Abstract: Graph-based multi-agent reinforcement learning (MARL) enables coordinated behavior under partial observability by modeling agents as nodes and commu

agentsarxiv-cs-lg

Bringing Clustering to MLL: Weakly-Supervised Clustering for Partial Multi-Label Learning

arXiv:2604.09359v1 Announce Type: new Abstract: Label noise in multi-label learning (MLL) poses significant challenges for model training, particularly in partial multi-label learning (PML) where cand

Building a Robust Documentation Agent with DigitalOcean Gradient AI Platform

DigitalOcean's Gradient AI Platform enables developers to build intelligent documentation agents that can automatically generate, maintain, and query technical documentation using large language model

agentsdigitalocean

Camera Artist: A Multi-Agent Framework for Cinematic Language Storytelling Video Generation

arXiv:2604.09195v1 Announce Type: new Abstract: We propose Camera Artist, a multi-agent framework that models a real-world filmmaking workflow to generate narrative videos with explicit cinematic lang

ChipSeek: Optimizing Verilog Generation via EDA-Integrated Reinforcement Learning

arXiv:2507.04736v2 Announce Type: replace Abstract: Large Language Models have emerged as powerful tools for automating Register-Transfer Level (RTL) code generation, yet they face critical limitation

Applications

CoMoVi: Co-Generation of 3D Human Motions and Realistic Videos

arXiv:2601.10632v2 Announce Type: replace Abstract: In this paper, we find that the generation of 3D human motions and 2D human videos is intrinsically coupled. 3D motions provide the structural prior

applicationsarxiv-cs-cv

Constraint-Aware Corrective Memory for Language-Based Drug Discovery Agents

arXiv:2604.09308v1 Announce Type: new Abstract: Large language models are making autonomous drug discovery agents increasingly feasible, but reliable success in this setting is not determined by any s

Decentralized Opinion-Integrated Decision making at Unsignalized Intersections via Signed Networks

arXiv:2604.09351v1 Announce Type: cross Abstract: In this letter, we consider the problem of decentralized decision making among connected autonomous vehicles at unsignalized intersections, where exis

agentsarxiv-cs-ro

Deep Light Pollution Removal in Night Cityscape Photographs

arXiv:2604.09145v1 Announce Type: new Abstract: Nighttime photography is severely degraded by light pollution induced by pervasive artificial lighting in urban environments. After long-range scatterin

Differentially Private and Federated Structure Learning in Bayesian Networks

arXiv:2512.01708v2 Announce Type: replace-cross Abstract: Learning the structure of a Bayesian network from decentralized data poses two major challenges: (i) ensuring rigorous privacy guarantees for

DiffHLS: Differential Learning for High-Level Synthesis QoR Prediction with GNNs and LLM Code Embeddings

arXiv:2604.09240v1 Announce Type: new Abstract: High-Level Synthesis (HLS) compiles C/C++ into RTL, but exploring pragma-driven optimization choices remains expensive because each design point require

Distributionally Robust Token Optimization in RLHF

arXiv:2604.08577v1 Announce Type: cross Abstract: Large Language Models (LLMs) tend to respond correctly to prompts that align to the data they were trained and fine-tuned on. Yet, small shifts in wor

Does AI respond better to the Carrot or the Stick?

This r/ChatGPT Reddit thread explores whether AI models like ChatGPT produce better outputs in response to positive, reward-based prompting ('carrot' approaches such as praise, incentives, or flattery

industryr-chatgpt

Emad Mostaque built Stable Diffusion. I asked him what the trillion-dollar AI labs won't say publicly. @EMostaque's answer: 'Soon, adding a …

Emad Mostaque built Stable Diffusion. I asked him what the trillion-dollar AI labs won't say publicly. @EMostaque's answer: 'Soon, adding a human to the best AI team will make it worse. Not slower. Ne

industryemad-mostaque--x

Every Response Counts: Quantifying Uncertainty of LLM-based Multi-Agent Systems through Tensor Decomposition

arXiv:2604.08708v1 Announce Type: cross Abstract: While Large Language Model-based Multi-Agent Systems (MAS) consistently outperform single-agent systems on complex tasks, their intricate interactions

Local Ai

From Frames to Events: Rethinking Evaluation in Human-Centric Video Anomaly Detection

arXiv:2604.09327v1 Announce Type: new Abstract: Pose-based Video Anomaly Detection (VAD) has gained significant attention for its privacy-preserving nature and robustness to environmental variations.

local-aiarxiv-cs-cv

Gen-n-Val: Agentic Image Data Generation and Validation

arXiv:2506.04676v2 Announce Type: replace-cross Abstract: The data scarcity, label noise, and long-tailed category imbalance remain important and unresolved challenges in many computer vision tasks, s

Get docs by MCP vs Web search

This Reddit post from r/ChatGPT discusses the trade-offs between retrieving documentation via an MCP (Model Context Protocol) server versus using traditional web search within AI workflows. The core c

agentsr-chatgpt

GNN-as-Judge: Unleashing the Power of LLMs for Graph Learning with GNN Feedback

arXiv:2604.08553v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown strong performance on text-attributed graphs (TAGs) due to their superior semantic understanding ability on te

Intel added 100B+ in value and now has a 300B+ market cap after its stock jumped 53% in nine sessions on plans to buy an Ireland fab and join Terafab (Bloomberg)

Bloomberg: Intel added 100B+ in value and now has a 300B+ market cap after its stock jumped 53% in nine sessions on plans to buy an Ireland fab and join Terafab — Intel Corp. has quickly become one of

industrytechmeme