Search: “models”

PhyMix: Towards Physically Consistent Single-Image 3D Indoor Scene Generation with Implicit--Explicit Optimization

arXiv:2604.10125v1 Announce Type: new Abstract: Existing single-image 3D indoor scene generators often produce results that look visually plausible but fail to obey real-world physics, limiting their

Safety

PICon: A Multi-Turn Interrogation Framework for Evaluating Persona Agent Consistency

DGX agent

arXiv:2603.25620v2 Announce Type: replace Abstract: Large language model (LLM)-based persona agents are rapidly being adopted as scalable proxies for human participants across diverse domains. Yet the

safetyarxiv-cs-cl

14 Apr 2026

PokeRL: Reinforcement Learning for Pokemon Red

model-releasesarxiv-cs-lg

arXiv:2604.10812v1 Announce Type: new Abstract: Pokemon Red is a long-horizon JRPG with sparse rewards, partial observability, and quirky control mechanics that make it a challenging benchmark for rei

Policy-Guided Threat Hunting: An LLM enabled Framework with Splunk SOC Triage

arXiv:2603.23966v3 Announce Type: replace-cross Abstract: With frequently evolving Advanced Persistent Threats (APTs) in cyberspace, traditional security solutions approaches have become inadequate fo

Policy Split: Incentivizing Dual-Mode Exploration in LLM Reinforcement with Dual-Mode Entropy Regularization

arXiv:2604.11510v1 Announce Type: cross Abstract: To encourage diverse exploration in reinforcement learning (RL) for large language models (LLMs) without compromising accuracy, we propose Policy Spli

safetyarxiv-cs-ai

PrefPaint: Enhancing Medical Image Inpainting through Expert Human Feedback

arXiv:2506.21834v2 Announce Type: replace Abstract: Inpainting, the process of filling missing or corrupted image parts, has broad applications in medical imaging. However, generating anatomically acc

researcharxiv-cs-cv

Agents

Privacy Against Agnostic Inference Attacks in Vertical Federated Learning

arXiv:2302.05545v4 Announce Type: replace-cross Abstract: A novel form of inference attack in vertical federated learning (VFL) is proposed, where two parties collaborate in training a machine learnin

agentsarxiv-cs-lg

Putting the Value Back in RL: Better Test-Time Scaling by Unifying LLM Reasoners With Verifiers

arXiv:2505.04842v2 Announce Type: replace-cross Abstract: Prevalent reinforcement learning~(RL) methods for fine-tuning LLM reasoners, such as GRPO or Leave-one-out PPO, abandon the learned value func

researcharxiv-cs-ai

QFS-Composer: Query-focused summarization pipeline for less resourced languages

arXiv:2604.10687v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong performance in text summarization, yet their effectiveness drops significantly across languages with res

safetyarxiv-cs-cl

QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits

arXiv:2604.10933v1 Announce Type: cross Abstract: Deep neural networks remain highly vulnerable to adversarial perturbations, limiting their reliability in security- and safety-critical applications.

safetyarxiv-cs-ai

Quotation-Based Data Retention Mechanism for Data Privacy in LLM-Empowered Network Services

arXiv:2503.23001v5 Announce Type: replace Abstract: The deployment of large language models (LLMs) for next-generation network optimization introduces novel data governance challenges. mobile network

ReContraster: Making Your Posters Stand Out with Regional Contrast

arXiv:2604.10442v1 Announce Type: new Abstract: Effective poster design requires rapidly capturing attention and clearly conveying messages. Inspired by the ``contrast effects'' principle, we propose

ReplicateAnyScene: Zero-Shot Video-to-3D Composition via Textual-Visual-Spatial Alignment

arXiv:2604.10789v1 Announce Type: new Abstract: Humans exhibit an innate capacity to rapidly perceive and segment objects from video observations, and even mentally assemble them into structured 3D sc

Representation-Aligned Multi-Scale Personalization for Federated Learning

arXiv:2604.11278v1 Announce Type: new Abstract: In federated learning (FL), accommodating clients with diverse resource constraints remains a significant challenge. A widely adopted approach is to use

Rethinking LLM Watermark Detection in Black-Box Settings: A Non-Intrusive Third-Party Framework

arXiv:2603.14968v2 Announce Type: replace-cross Abstract: While watermarking serves as a critical mechanism for LLM provenance, existing secret-key schemes tightly couple detection with injection, req

safetyarxiv-cs-cl

Rethinking Video Human-Object Interaction: Set Prediction over Time for Unified Detection and Anticipation

arXiv:2604.10397v1 Announce Type: cross Abstract: Video-based human-object interaction (HOI) understanding requires both detecting ongoing interactions and anticipating their future evolution. However

Revisiting the Scale Loss Function and Gaussian-Shape Convolution for Infrared Small Target Detection

arXiv:2604.09991v1 Announce Type: new Abstract: Infrared small target detection still faces two persistent challenges: training instability from non-monotonic scale loss functions, and inadequate spat

Rhizome OS-1: Rhizome's Semi-Autonomous Operating System for Small Molecule Drug Discovery

arXiv:2604.07512v2 Announce Type: replace Abstract: We present Rhizome OS-1, a semi-autonomous operating system for small molecule drug discovery in which multi-modal AI agents operate as a full multi

RL-Driven Sustainable Land-Use Allocation for the Lake Malawi Basin

arXiv:2604.03768v2 Announce Type: replace Abstract: Unsustainable land-use practices in ecologically sensitive regions threaten biodiversity, water resources, and the livelihoods of millions. This pap

Scalable Stewardship of an LLM-Assisted Clinical Benchmark with Physician Oversight

arXiv:2512.19691v3 Announce Type: replace Abstract: Reference labels for machine-learning benchmarks are increasingly synthesized with LLM assistance, but their reliability remains underexamined. We a

Scaling unstructured enterprise knowledge with BigQuery Graph, and Kineviz GraphXR

model-releasesgoogle-cloud-ai

Over 80% of enterprise data lives in unstructured form — PDFs, emails, reports, regulatory filings. Most of the time, such sources contain critical business information, yet they remain difficult to a

Simple but Stable, Fast and Safe: Achieve End-to-end Control by High-Fidelity Differentiable Simulation

model-releasesarxiv-cs-ro

arXiv:2604.10548v1 Announce Type: new Abstract: Obstacle avoidance is a fundamental vision-based task essential for enabling quadrotors to perform advanced applications. When planning the trajectory,

Single-Agent LLMs Outperform Multi-Agent Systems on Multi-Hop Reasoning Under Equal Thinking Token Budgets

model-releasesarxiv-cs-cl

arXiv:2604.02460v2 Announce Type: replace Abstract: Recent work reports strong performance from multi-agent LLM systems (MAS), but these gains are often confounded by increased test-time computation.

Source: Anthropic is preparing to release Claude Opus 4.7, along with a new AI-powered tool for designing websites and presentations, as soon as this week (Stephanie Palazzolo/The Information)

Stephanie Palazzolo / The Information: Source: Anthropic is preparing to release Claude Opus 4.7, along with a new AI-powered tool for designing websites and presentations, as soon as this week — Anth

model-releasestechmeme

Sources: at least two US federal agencies and three congressional committees have reached out to Anthropic to test Claude Mythos, quietly bypassing Trump's ban (Politico)

Politico: Sources: at least two US federal agencies and three congressional committees have reached out to Anthropic to test Claude Mythos, quietly bypassing Trump's ban — The Commerce Department's Ce

model-releasestechmeme

SpectralLoRA: Is Low-Frequency Structure Sufficient for LoRA Adaptation? A Spectral Analysis of Weight Updates

arXiv:2604.10649v1 Announce Type: cross Abstract: We present a systematic empirical study of the spectral structure of LoRA weight updates. Through 2D Discrete Cosine Transform (DCT) analysis of train

researcharxiv-cs-cl

Spoiler Alert: Narrative Forecasting as a Metric for Tension in LLM Storytelling

model-releasesarxiv-cs-cl

arXiv:2604.09854v1 Announce Type: new Abstract: LLMs have so far failed both to generate consistently compelling stories and to recognize this failure--on the leading creative-writing benchmark (EQ-Be

SymphoMotion: Joint Control of Camera Motion and Object Dynamics for Coherent Video Generation

arXiv:2604.03723v2 Announce Type: replace Abstract: Controlling both camera motion and object dynamics is essential for coherent and expressive video generation, yet current methods typically handle o

Hardware

Tessera: Unlocking Heterogeneous GPUs through Kernel-Granularity Disaggregation

arXiv:2604.10180v1 Announce Type: cross Abstract: Disaggregation maps parts of an AI workload to different types of GPUs, offering a path to utilize modern heterogeneous GPU clusters. However, existin

hardwarearxiv-cs-lg

The Amazing Agent Race: Strong Tool Users, Weak Navigators

arXiv:2604.10261v1 Announce Type: new Abstract: Existing tool-use benchmarks for LLM agents are overwhelmingly linear: our analysis of six benchmarks shows 55 to 100% of instances are simple chains of

Applications

The Deployment Gap in AI Media Detection: Platform-Aware and Visually Constrained Adversarial Evaluation

arXiv:2604.09706v1 Announce Type: cross Abstract: Recent AI media detectors report near-perfect performance under clean laboratory evaluation, yet their robustness under realistic deployment condition

applicationsarxiv-cs-ai

The LLM tunes its own llama.cpp flags (+54% tok/s on Qwen3.5-27B)

This r/ollama post describes a technique where an LLM is used to automatically tune its own llama.cpp runtime flags — such as parameters related to GPU offloading, KV cache quantization, batch sizes,

model-releasesr-ollama

The Past Is Not Past: Memory-Enhanced Dynamic Reward Shaping

arXiv:2604.11297v1 Announce Type: cross Abstract: Despite the success of reinforcement learning for large language models, a common failure mode is reduced sampling diversity, where the policy repeate

safetyarxiv-cs-ai

There are multiple realities of AI right now. And what you have access to drastically changes your workflows, trust in AI, and ability to ad…

model-releasesallie-k--miller--x

There are multiple realities of AI right now. And what you have access to drastically changes your workflows, trust in AI, and ability to adapt to the future. Here’s the briefest state of the AI world

Think Before you Write: QA-Guided Reasoning for Character Descriptions in Books

arXiv:2604.11435v1 Announce Type: cross Abstract: Character description generation is an important capability for narrative-focused applications such as summarization, story analysis, and character-dr

researcharxiv-cs-ai

Agents

Thoth v3.14.0: multi-provider cloud and multi-provider image generation. Five cloud providers now work as first-class citizens: OpenAI, Anth…

Thoth v3.14.0: multi-provider cloud and multi-provider image generation. Five cloud providers now work as first-class citizens: OpenAI, Anthropic, Google, xAI, and OpenRouter. Image generation spans t

agentsharrison-chase--x

Time is Not a Label: Continuous Phase Rotation for Temporal Knowledge Graphs and Agentic Memory

arXiv:2604.11544v1 Announce Type: cross Abstract: Structured memory representations such as knowledge graphs are central to autonomous agents and other long-lived systems. However, most existing appro

Token-Budget-Aware Pool Routing for Cost-Efficient LLM Inference

arXiv:2604.09613v1 Announce Type: cross Abstract: Production vLLM fleets provision every instance for worst-case context length, wasting 4-8x concurrency on the 80-95% of requests that are short and s

Training-Free Multi-User Generative Semantic Communications via Null-Space Diffusion Sampling

arXiv:2405.09866v2 Announce Type: replace-cross Abstract: In recent years, novel communication strategies have emerged to face the challenges that the increased number of connected devices and the hig

Trustworthy Feature Importance Avoids Unrestricted Permutations

arXiv:2604.11253v1 Announce Type: cross Abstract: Feature importance methods using unrestricted permutations are flawed due to extrapolation errors; such errors appear in all non-trivial variable impo

Turing Test on Screen: A Benchmark for Mobile GUI Agent Humanization

arXiv:2604.09574v1 Announce Type: new Abstract: The rise of autonomous GUI agents has triggered adversarial countermeasures from digital platforms, yet existing research prioritizes utility and robust

Uncertainty-quantified Pulse Signal Recovery from Facial Video using Regularized Stochastic Interpolants

arXiv:2604.10777v1 Announce Type: new Abstract: Imaging Photoplethysmography (iPPG), an optical procedure which recovers a human's blood volume pulse (BVP) waveform using pixel readout from a camera,

Unified Removal of Raindrops and Reflections: A New Benchmark and A Novel Pipeline

arXiv:2603.16446v3 Announce Type: replace Abstract: When capturing images through glass surfaces or windshields on rainy days, raindrops and reflections frequently co-occur to significantly reduce the

Unifying Ontology Construction and Semantic Alignment for Deterministic Enterprise Reasoning at Scale

arXiv:2604.09608v1 Announce Type: new Abstract: While enterprises amass vast quantities of data, much of it remains chaotic and effectively dormant, preventing decision-making based on comprehensive i

Tutorials

Unmixing-Guided Spatial-Spectral Mamba with Clustering Tokens for Hyperspectral Image Classification

arXiv:2604.09948v1 Announce Type: new Abstract: Although hyperspectral image (HSI) classification is critical for supporting various environmental applications, it is a challenging task due to the spe

tutorialsarxiv-cs-cv

Unsupervised Domain Adaptation for Binary Classification with an Unobservable Source Subpopulation

model-releasesarxiv-cs-lg

arXiv:2509.20587v3 Announce Type: replace-cross Abstract: We study an unsupervised domain adaptation problem where the source domain consists of subpopulations defined by the binary label Y and a bina

VGGT-HPE: Reframing Head Pose Estimation as Relative Pose Prediction

arXiv:2604.10106v1 Announce Type: new Abstract: Monocular head pose estimation is traditionally formulated as direct regression from a single image to an absolute pose. This paradigm forces the networ

Volumetric Ergodic Control

arXiv:2511.11533v3 Announce Type: replace-cross Abstract: Ergodic control synthesizes optimal coverage behaviors over spatial distributions for nonlinear systems. However, existing formulations model

researcharxiv-cs-ai