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No More Stale Feedback: Co-Evolving Critics for Open-World Agent Learning

arXiv:2601.06794v2 Announce Type: replace Abstract: Critique-guided reinforcement learning (RL) has emerged as a powerful paradigm for training LLM agents by augmenting sparse outcome rewards with nat

safetyarxiv-cs-ai

Tutorials

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Human DGX agent

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NoisePrints: Distortion-Free Watermarks for Authorship in Private Diffusion Models

DGX agent

arXiv:2510.13793v2 Announce Type: replace Abstract: With the rapid adoption of diffusion models for visual content generation, proving authorship and protecting copyright have become critical. This ch

tutorialsarxiv-cs-cv

15 Apr 2026

Not All Turns Are Equally Hard: Adaptive Thinking Budgets For Efficient Multi-Turn Reasoning

arXiv:2604.05164v2 Announce Type: replace-cross Abstract: As LLM reasoning performance plateau, improving inference-time compute efficiency is crucial to mitigate overthinking and long thinking traces

safetyarxiv-cs-ai

NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: Professional Image Quality Assessment (Track 1)

arXiv:2604.12512v1 Announce Type: cross Abstract: In this paper, we present an overview of the NTIRE 2026 challenge on the 3rd Restore Any Image Model in the Wild, specifically focusing on Track 1: Pr

Nucleus-Image: Sparse MoE for Image Generation

model-releasesarxiv-cs-cv

arXiv:2604.12163v1 Announce Type: new Abstract: We present Nucleus-Image, a text-to-image generation model that establishes a new Pareto frontier in quality-versus-efficiency by matching or exceeding

Observing the unobserved confounding through its effects: toward randomized trial-like estimates from real-world survival data

arXiv:2604.12137v1 Announce Type: cross Abstract: Background: Randomized controlled trials (RCTs) are costly, time-consuming, and often infeasible, while treatment-effect estimation from observational

Obtaining Partition Crossover masks using Statistical Linkage Learning for solving noised optimization problems with hidden variable dependency structure

arXiv:2604.11862v1 Announce Type: cross Abstract: In optimization problems, some variable subsets may have a joint non-linear or non-monotonical influence on the function value. Therefore, knowledge o

applicationsarxiv-cs-lg

Agents

OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning

arXiv:2502.11271v2 Announce Type: replace-cross Abstract: Solving complex reasoning tasks may involve visual understanding, domain knowledge retrieval, numerical calculation, and multi-step reasoning.

agentsarxiv-cs-cl

OFA-Diffusion Compression: Compressing Diffusion Model in One-Shot Manner

model-releasesarxiv-cs-cv

arXiv:2604.12668v1 Announce Type: new Abstract: The Diffusion Probabilistic Model (DPM) achieves remarkable performance in image generation, while its increasing parameter size and computational overh

Offline-Online Reinforcement Learning for Linear Mixture MDPs

arXiv:2604.11994v1 Announce Type: new Abstract: We study offline-online reinforcement learning in linear mixture Markov decision processes (MDPs) under environment shift. In the offline phase, data ar

safetyarxiv-cs-lg

Olmo 3

model-releasesarxiv-cs-cl

arXiv:2512.13961v2 Announce Type: replace Abstract: We introduce Olmo 3, a family of state-of-the-art, fully-open language models at the 7B and 32B parameter scales. Olmo 3 model construction targets

OmniFood8K: Single-Image Nutrition Estimation via Hierarchical Frequency-Aligned Fusion

arXiv:2604.12356v1 Announce Type: new Abstract: Accurate estimation of food nutrition plays a vital role in promoting healthy dietary habits and personalized diet management. Most existing food datase

OmniHands: Towards Robust 4D Hand Mesh Recovery via A Versatile Transformer

arXiv:2405.20330v4 Announce Type: replace-cross Abstract: In this paper, we introduce OmniHands, a universal approach to recovering interactive hand meshes and their relative movement from monocular o

On Efficient Variants of Segment Anything Model: A Survey

arXiv:2410.04960v5 Announce Type: replace Abstract: The Segment Anything Model (SAM) is a foundational model for image segmentation tasks, known for its strong generalization across diverse applicatio

On Higher-Order Geometric Refinements of Classical Covariance Asymptotics: An Approach via Intrinsic and Extrinsic Information Geometry

arXiv:2604.12725v1 Announce Type: cross Abstract: Classical Fisher-information asymptotics describe the covariance of regular efficient estimators through the local quadratic approximation of the log-

On the continuum limit of t-SNE for data visualization

arXiv:2604.12041v1 Announce Type: cross Abstract: This work is concerned with the continuum limit of a graph-based data visualization technique called the t-Distributed Stochastic Neighbor Embedding (

On the Convergence Analysis of Muon

arXiv:2505.23737v2 Announce Type: replace-cross Abstract: The majority of parameters in neural networks are naturally represented as matrices. However, most commonly used optimizers treat these matrix

researcharxiv-cs-lg

On the Geometry of Receiver Operating Characteristic and Precision-Recall Curves

arXiv:2504.02169v3 Announce Type: replace-cross Abstract: We study the geometry of Receiver Operating Characteristic (ROC) and Precision-Recall (PR) curves in binary classification problems. The key f

On the Mathematical Relationship Between Layer Normalization and Dynamic Activation Functions

arXiv:2503.21708v4 Announce Type: replace-cross Abstract: Layer normalization (LN) is an essential component of modern neural networks. While many alternative techniques have been proposed, none of th

One Model for All: Unified Try-On and Try-Off in Any Pose via LLM-Inspired Bidirectional Tweedie Diffusion

arXiv:2508.04559v3 Announce Type: replace Abstract: Recent diffusion-based approaches have made significant advances in image-based virtual try-on, enabling more realistic and end-to-end garment synth

One Token Away from Collapse: The Fragility of Instruction-Tuned Helpfulness

arXiv:2604.13006v1 Announce Type: cross Abstract: Instruction-tuned large language models produce helpful, structured responses, but how robust is this helpfulness when trivially constrained? We show

One View Is Enough! Monocular Training for In-the-Wild Novel View Generation

arXiv:2603.23488v2 Announce Type: replace Abstract: Monocular novel-view synthesis has long required multi-view image pairs for supervision, limiting training data scale and diversity. We argue it is

OpenTME: An Open Dataset of AI-powered H&E Tumor Microenvironment Profiles from TCGA

arXiv:2604.12075v1 Announce Type: cross Abstract: The tumor microenvironment (TME) plays a central role in cancer progression, treatment response, and patient outcomes, yet large-scale, consistent, an

Operationalising the Right to be Forgotten in LLMs: A Lightweight Sequential Unlearning Framework for Privacy-Aligned Deployment in Politically Sensitive Environments

arXiv:2604.12459v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in politically sensitive environments, where memorisation of personal data or confidential conten

Orthogonal Subspace Projection for Continual Machine Unlearning via SVD-Based LoRA

arXiv:2604.12526v1 Announce Type: cross Abstract: Continual machine unlearning aims to remove the influence of data that should no longer be retained, while preserving the usefulness of the model on e

OSC: Hardware Efficient W4A4 Quantization via Outlier Separation in Channel Dimension

arXiv:2604.12782v1 Announce Type: cross Abstract: While 4-bit quantization is essential for high-throughput deployment of Large Language Models, activation outliers often lead to significant accuracy

Agents

OVAL: Open-Vocabulary Augmented Memory Model for Lifelong Object Goal Navigation

arXiv:2604.12872v1 Announce Type: new Abstract: Object Goal Navigation (ObjectNav) refers to an agent navigating to an object in an unseen environment, which is an ability often required in the accomp

agentsarxiv-cs-ro

PAINT: Partner-Agnostic Intent-Aware Cooperative Transport with Legged Robots

arXiv:2604.12852v1 Announce Type: new Abstract: Collaborative transport requires robots to infer partner intent through physical interaction while maintaining stable loco-manipulation. This becomes pa

safetyarxiv-cs-ro

PAL: Personal Adaptive Learner

arXiv:2604.13017v1 Announce Type: new Abstract: AI-driven education platforms have made some progress in personalisation, yet most remain constrained to static adaptation--predefined quizzes, uniform

Parallax: Why AI Agents That Think Must Never Act

arXiv:2604.12986v1 Announce Type: cross Abstract: Autonomous AI agents are rapidly transitioning from experimental tools to operational infrastructure, with projections that 80% of enterprise applicat

safetyarxiv-cs-ai

Parametric Interpolation of Dynamic Mode Decomposition for Predicting Nonlinear Systems

arXiv:2604.12103v1 Announce Type: cross Abstract: We present parameter-interpolated dynamic mode decomposition (piDMD), a parametric reduced-order modeling framework that embeds known parameter-affine

Parcae: Scaling Laws For Stable Looped Language Models

arXiv:2604.12946v1 Announce Type: new Abstract: Traditional fixed-depth architectures scale quality by increasing training FLOPs, typically through increased parameterization, at the expense of a high

ParetoBandit: Budget-Paced Adaptive Routing for Non-Stationary LLM Serving

model-releasesarxiv-cs-cl

arXiv:2604.00136v2 Announce Type: replace-cross Abstract: Multi-model LLM serving operates in a non-stationary, noisy environment: providers revise pricing, model quality can shift or regress without

Local Ai

PC-MIL: Decoupling Feature Resolution from Supervision Scale in Whole-Slide Learning

arXiv:2604.12100v1 Announce Type: new Abstract: Whole-slide image (WSI) classification in computational pathology is commonly formulated as slide-level Multiple Instance Learning (MIL) with a single g

local-aiarxiv-cs-cv

PDF-GS: Progressive Distractor Filtering for Robust 3D Gaussian Splatting

arXiv:2604.12580v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have enabled impressive real-time photorealistic rendering. However, conventional training pipelines inh

Perception-Aware Policy Optimization for Multimodal Reasoning

arXiv:2507.06448v5 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has proven to be a highly effective strategy for endowing Large Language Models (LLMs) with ro

safetyarxiv-cs-cl

Physically Accurate Rigid-Body Dynamics in Particle-Based Simulation

model-releasesarxiv-cs-ro

arXiv:2603.14634v3 Announce Type: replace Abstract: Robotics demands simulation that can reason about the diversity of real-world physical interactions, from rigid to deformable objects and fluids. Cu

Physics-Grounded Monocular Vehicle Distance Estimation Using Standardized License Plate Typography

arXiv:2604.12239v1 Announce Type: new Abstract: Accurate inter-vehicle distance estimation is a cornerstone of Advanced Driver Assistance Systems (ADAS) and autonomous driving. While LiDAR and radar p

safetyarxiv-cs-cv

Pi-HOC: Pairwise 3D Human-Object Contact Estimation

arXiv:2604.12923v1 Announce Type: new Abstract: Resolving real-world human-object interactions in images is a many-to-many challenge, in which disentangling fine-grained concurrent physical contact is

PianoFlow: Music-Aware Streaming Piano Motion Generation with Bimanual Coordination

arXiv:2604.12856v1 Announce Type: new Abstract: Audio-driven bimanual piano motion generation requires precise modeling of complex musical structures and dynamic cross-hand coordination. However, exis

Pictorial and apictorial polygonal jigsaw puzzles from arbitrary number of crossing cuts

arXiv:2008.07644v3 Announce Type: replace-cross Abstract: Jigsaw puzzle solving, the problem of constructing a coherent whole from a set of non-overlapping unordered visual fragments, is fundamental t

PILOT: Planning via Internalized Latent Optimization Trajectories for Large Language Models

arXiv:2601.19917v2 Announce Type: replace Abstract: Strategic planning is critical for multi-step reasoning, yet compact Large Language Models (LLMs) often lack the capacity to formulate global strate

researcharxiv-cs-cl

Hardware

PipeLive: Efficient Live In-place Pipeline Parallelism Reconfiguration for Dynamic LLM Serving

arXiv:2604.12171v1 Announce Type: cross Abstract: Pipeline parallelism (PP) is widely used to partition layers of large language models (LLMs) across GPUs, enabling scalable inference for large models

hardwarearxiv-cs-lg

Point Prompting: Counterfactual Tracking with Video Diffusion Models

arXiv:2510.11715v2 Announce Type: replace Abstract: Trackers and video generators solve closely related problems: the former analyze motion, while the latter synthesize it. We show that this connectio

Poisoning the Inner Prediction Logic of Graph Neural Networks for Clean-Label Backdoor Attacks

arXiv:2603.05004v2 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have achieved remarkable results in various tasks. Recent studies reveal that graph backdoor attacks can poison t

Policy-Invisible Violations in LLM-Based Agents

arXiv:2604.12177v1 Announce Type: new Abstract: LLM-based agents can execute actions that are syntactically valid, user-sanctioned, and semantically appropriate, yet still violate organizational polic

PolicyLLM: Towards Excellent Comprehension of Public Policy for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2604.12995v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly integrated into real-world decision-making, including in the domain of public policy. Yet, their ability t

Polynomial Expansion Rank Adaptation: Enhancing Low-Rank Fine-Tuning with High-Order Interactions

arXiv:2604.11841v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) is a widely used strategy for efficient fine-tuning of large language models (LLMs), but its strictly linear structure fund