All entries

Principled Synthetic Data Enables the First Scaling Laws for LLMs in Recommendation

arXiv:2602.07298v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) represent a promising frontier for recommender systems, yet their development has been impeded by the absence of

Tutorials

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Prior-Guided Multi-Omic Transformers for Single-Cell Gene Regulatory Network Inference

DGX agent

arXiv:2606.00685v1 Announce Type: new Abstract: Gene regulatory networks (GRNs) capture transcription factor-target interactions and are central to understanding cell-state regulation and disease. Rec

tutorialsarxiv-cs-lg

2 Jun 2026

PRISM: Gauge-Invariant Tangent-Space Differentially Private LoRA

arXiv:2606.00944v1 Announce Type: new Abstract: Applying differential privacy (DP) via DP-SGD to Low-Rank Adaptation (LoRA) is a natural approach for privacy-preserving fine-tuning. However, LoRA's lo

researcharxiv-cs-lg

PrivacyPeek: Auditing What LLM-Based Agents Acquire, Not Just What They Say

arXiv:2606.00152v1 Announce Type: cross Abstract: LLM-based agents are rapidly advancing, autonomously invoking external tools to complete multi-step tasks for users. However, agents often acquire mor

Private and Stable Test-Time Adaptation with Differential Privacy

arXiv:2606.01908v1 Announce Type: cross Abstract: Test-time adaptation (TTA) can reduce error on new and different data by updating the model on these inputs during inference. However, these updates r

researcharxiv-cs-cv

Proactive-reactive detection and mitigation of intermittent faults in robot swarms

arXiv:2509.19246v2 Announce Type: replace Abstract: Intermittent faults are transient errors that sporadically appear and disappear. Although intermittent faults pose substantial challenges to reliabi

researcharxiv-cs-ro

ProactiveLLM: Learning Active Interaction for Streaming Large Language Models

arXiv:2606.00523v1 Announce Type: new Abstract: Standard Large Language Models (LLMs) follow a read-then-generate paradigm, causing unnecessary latency and computation. Streaming LLMs alleviate this i

local-aiarxiv-cs-cl

Probabilistic Performance Guarantees for Multi-Task Reinforcement Learning

arXiv:2602.02098v2 Announce Type: replace-cross Abstract: Multi-task reinforcement learning trains generalist policies that can execute multiple tasks. While recent years have seen significant progres

Probe Before You Edit: Probing-Guided Molecular Optimization for LLM Agents in Structure-Based Drug Design

arXiv:2606.00555v1 Announce Type: new Abstract: Structure-based drug design increasingly employs LLM agents to iteratively refine ligands against a target pocket, yet a viable ligand must satisfy two

ProbeScale: Probing Analysis to Optimize Neural Scaling Laws for Efficient Small Language Model Inference

arXiv:2606.01806v1 Announce Type: cross Abstract: Small Language Models (SLMs) offer a balance between capability and computational feasibility. Neural scaling laws inform their optimal training, sugg

ProbMoE: Differentiable Probabilistic Routing for Mixture-of-Experts

arXiv:2606.01509v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models scale by activating only a small subset of experts per token. However, training such models remains challenging becaus

researcharxiv-cs-ai

ProbRes: Volatility Learning for Probabilistic Time-Series Forecasting

arXiv:2606.02117v1 Announce Type: cross Abstract: Probabilistic time series forecasting has attracted increasing attention in financial applications due to the need to quantify risk and uncertainty in

applicationsarxiv-cs-lg

Product-Aware Deep Autoencoders for Robust Process Monitoring in Multi-Product Cyber-Physical Systems

arXiv:2606.00052v1 Announce Type: new Abstract: As Industry 4.0 accelerates the integration of Cyber-Physical Systems (CPS) in manufacturing, robust anomaly detection has become critical for ensuring

ProductWebGen: Benchmarking Multimodal Product Webpage Generation

arXiv:2606.01022v1 Announce Type: cross Abstract: Crafting a product display webpage from a source product image, along with layout and visual content instructions, holds significant practical value f

Profiling Privacy Preservation Against Gradient Inversion Attacks in Tabular Federated Learning

arXiv:2606.00986v1 Announce Type: new Abstract: Federated learning (FL) enables multiple data holders to train machine learning models collaboratively without centralizing raw data, making it useful i

Project SPARROW and the Future of Conservation Technology

arXiv:2606.00108v1 Announce Type: cross Abstract: Global biodiversity is declining at unprecedented rates, yet the tools available to monitor and protect ecosystems remain limited by constraints in po

ProjQ: Project-and-Quantize for Adapter-Aware LLM Compression

arXiv:2606.00494v1 Announce Type: new Abstract: Post-Training Quantization (PTQ) and Low-Rank Adaptation (LoRA) constitute the standard pipeline for efficient Large Language Model (LLM) deployment. Ho

Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach

arXiv:2606.01012v1 Announce Type: new Abstract: AI for materials science is a critical topic within AI for science, aiming to accelerate materials discovery and produce accurate property predictions.

applicationsarxiv-cs-ai

PropLLM: Propagation-Aware Scene Reconstruction for Network Fault Diagnosis

arXiv:2606.00582v1 Announce Type: new Abstract: Network faults propagate layer by layer along topology and protocol dependencies, yet operations systems typically observe only symptomatic alerts at th

Prospect-Theory Behavior from Bellman Optimality in MDPs with Catastrophic States

arXiv:2606.00970v1 Announce Type: new Abstract: We study risk-neutral control in Markov decision processes with an absorbing catastrophic state. Even though rewards are linear and the agent has no uti

ProtoAda: Prototype-Guided Adaptive Adapter Expansion and Geometric Consolidation for Multimodal Continual Instruction Tuning

arXiv:2606.02576v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) achieve strong performance through instruction tuning, but real-world deployment requires them to continually a

applicationsarxiv-cs-cv

Prototype Selection Using Topological Data Analysis

arXiv:2511.04873v2 Announce Type: replace-cross Abstract: Prototype selection methods compress a training set, but the existing taxonomy of condensation, edition, hybrid, competence-based, optimizatio

researcharxiv-cs-lg

Prototype Transformer: Towards Language Model Architectures Interpretable by Design

arXiv:2602.11852v2 Announce Type: replace Abstract: While state-of-the-art language models (LMs) surpass most humans in certain domains, their reasoning remains largely opaque, reducing trust and incr

Prototypicality Bias Reveals Blindspots in Multimodal Evaluation Metrics

arXiv:2601.04946v3 Announce Type: replace-cross Abstract: Automatic metrics are widely used to evaluate text-to-image models, often replacing human judgment in benchmarking, model selection, and large

ProtStructQA: A Denotation Threshold in Protein Structural Reasoning

model-releasesarxiv-cs-cl

arXiv:2606.00451v1 Announce Type: new Abstract: Protein-language systems are often evaluated by whether they generate plausible biological text, but a structural question has a sharper semantics: it d

Provable Data Scaling Law for Meta Learning via Complexity Minimization

arXiv:2606.02008v1 Announce Type: cross Abstract: Pre-training has become a fundamental paradigm in modern machine learning, with one of its key empirical benefits being reduced downstream sample comp

researcharxiv-cs-lg

PSG-Nav: Probabilistic Scene Graph Navigation via Multiverse Decision Making

arXiv:2606.01313v1 Announce Type: cross Abstract: Open-vocabulary navigation requires embodied agents to manage significant perception uncertainty stemming from semantic ambiguity and model errors. Ho

researcharxiv-cs-ai

PUMA: Layer-Pruned Language Model for Efficient Unified Multimodal Retrieval with Modality-Adaptive Learning

model-releasesarxiv-cs-cv

arXiv:2507.08064v3 Announce Type: replace-cross Abstract: As multimedia content expands, the demand for unified multimodal retrieval (UMR) in real-world applications increases. Recent work leverages m

Quality Audio Prototyping: a prototype system for unified sound retrieval and procedural generation

arXiv:2606.00629v1 Announce Type: cross Abstract: Sound design workflows frequently oscillate between time-consuming library searches and the complexity of procedural synthesis, with practitioners typ

Quality-Diversity Evolution for Discovering Diverse Vulnerabilities in LLM Safety

model-releasesarxiv-cs-cl

arXiv:2606.00801v1 Announce Type: cross Abstract: Current approaches to LLM adversarial testing suffer from coverage gaps: manual red-teaming does not scale, LLM-as-attacker methods exhibit mode colla

Quality-Guided Semi-Supervised Learning for Medical Image Segmentation

arXiv:2606.01753v1 Announce Type: new Abstract: Training accurate medical image segmentation models requires large amounts of densely annotated data, which is costly and time-consuming to obtain. Semi

researcharxiv-cs-cv

Quantifying the Energy Floor: Direct Measurement and Replay Buffer Bias in SAC-Based HVAC Control on sbsim

arXiv:2606.01665v1 Announce Type: new Abstract: We quantify the energy floor -- the minimum achievable cost given action space constraints -- for Soft Actor-Critic (SAC) HVAC control on the sbsim cali

Quantifying the Salience of Geo-Cultural Values for Pluralistic Safety Alignment

arXiv:2606.00369v1 Announce Type: cross Abstract: Safe global deployment of AI models requires alignment with human values that vary across cultures. Yet rater pools in safety evaluation datasets rema

safetyarxiv-cs-lg

Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video

arXiv:2606.02301v1 Announce Type: cross Abstract: Chronic pain diminishes quality of life by decreasing functional ability, yet objectively measuring this functional impact remains challenging in real

Quantized Reasoning Models Think They Need to Think Longer, but They Do Not

arXiv:2606.00206v1 Announce Type: new Abstract: Post-training quantization (PTQ) is widely used to deploy large language models efficiently, but its effect on reasoning models is not well understood.

applicationsarxiv-cs-lg

Quantum Algorithm for Distributed Reduction of Entanglements (QADR): A Trainable and Simulation-Efficient QML Framework

arXiv:2606.01291v1 Announce Type: cross Abstract: Training Variational Quantum Circuits (VQCs) under Noisy Intermediate-Scale Quantum (NISQ) constraints introduces severe computational limitations: cl

Quantum Reservoir Computing and Risk Bounds

arXiv:2501.08640v2 Announce Type: replace Abstract: We propose a way to bound the generalisation errors of several classes of quantum reservoirs using the Rademacher complexity. We give specific, para

Quantum Tunneling-Aware Machine Learning: Physics-Derived Noise Models for Robust Deployment

arXiv:2606.00741v1 Announce Type: cross Abstract: Transistor scaling is approaching a quantum-mechanical limit, as thin gate oxides induce electron leakage through quantum tunneling. Unlike convention

researcharxiv-cs-ai

Hardware

Quartet II: Accurate LLM Pre-Training in NVFP4 by Improved Unbiased Gradient Estimation

arXiv:2601.22813v2 Announce Type: replace Abstract: The NVFP4 lower-precision format, supported in hardware by NVIDIA Blackwell GPUs, promises to allow, for the first time, end-to-end fully-quantized

hardwarearxiv-cs-lg

Query Circuits: Explaining How Language Models Answer User Prompts

arXiv:2509.24808v2 Announce Type: replace Abstract: Explaining why a language model produces a particular output requires local, input-level explanations. Existing methods uncover global capability ci

Query-Limited Community Recovery in Stochastic Block Models

arXiv:2606.02055v1 Announce Type: cross Abstract: We study exact community recovery in the two-community stochastic block model on n vertices under limited and noisy access to network data. The learne

Question-Aware Evidence Ledgers for Video Relational Reasoning

model-releasesarxiv-cs-cv

arXiv:2606.02506v1 Announce Type: new Abstract: The VRR-QA challenge evaluates visual relational reasoning in videos, where answers often depend on implicit spatial relations, event boundaries, target

R2-Router: A New Paradigm for LLM Routing with Reasoning

arXiv:2602.02823v2 Announce Type: replace Abstract: As LLMs proliferate with diverse capabilities and costs, LLM routing has emerged by learning to predict each LLM's quality and cost for a given quer

researcharxiv-cs-cl

R^3: Composed Video Retrieval via Reasoning-Guided Recalling and Re-ranking

arXiv:2606.01113v1 Announce Type: new Abstract: The CoVR-R challenge evaluates composed video retrieval, where a system must retrieve a target video from a large gallery given a reference video and a

researcharxiv-cs-cv

RA-LWLM: Retrieval-Augmented In-Context Localization with Wireless Foundation Models

arXiv:2606.01899v1 Announce Type: cross Abstract: Wireless localization is a fundamental capability of sixth-generation (6G) networks. Conventional model-based methods require accurate modeling of the

Agents

RadAgent: A tool-using AI agent for stepwise interpretation of chest computed tomography

arXiv:2604.15231v2 Announce Type: replace Abstract: Vision-language models (VLM) have markedly advanced AI-driven interpretation and reporting of complex medical imaging, such as computed tomography (

agentsarxiv-cs-ai

RADE: Random Add-Drop Edge as a Regularizer

arXiv:2606.00757v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) suffer from overfitting and over-squashing of long-range information. Stochastic graph augmentations (e.g., edge deletion)

safetyarxiv-cs-lg

RadioMaster: Multi-Agent System for Autonomous Radio Signal Generation

arXiv:2606.01862v1 Announce Type: cross Abstract: Translating user intents into physical radio signals represents the critical yet notoriously tedious final step in wireless prototyping, as it require