Search: “framework”

On the Generalization Gap in Self-Evolving Language Model Reasoning

model-releasesarxiv-cs-cl

arXiv:2606.01075v1 Announce Type: new Abstract: Recent work suggests that large language models (LLMs) can improve through self-evolution (SE), using supervision signals generated by the model itself.

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OncoReason: Structuring Clinical Reasoning in LLMs for Robust and Interpretable Survival Prediction

DGX agent

arXiv:2510.17532v2 Announce Type: replace Abstract: Predicting cancer treatment outcomes requires models that are both accurate and interpretable, particularly in the presence of heterogeneous clinica

model-releasesarxiv-cs-cl

2 Jun 2026

OPD+: Rethinking the Advantage Design for On-Policy Distillation

arXiv:2606.01039v1 Announce Type: cross Abstract: On-policy distillation (OPD) is a widely used technique to transfer capabilities from capable teacher language models to the base student models, and

OpenDPR: Open-Vocabulary Change Detection via Vision-Centric Diffusion-Guided Prototype Retrieval for Remote Sensing Imagery

model-releasesarxiv-cs-cv

arXiv:2603.27645v2 Announce Type: replace Abstract: Open-vocabulary change detection (OVCD) seeks to recognize arbitrary changes of interest by enabling generalization beyond a fixed set of predefined

Optimizing Diversity and Quality through Base-Aligned Model Collaboration

arXiv:2511.05650v2 Announce Type: replace-cross Abstract: Alignment has greatly improved large language models (LLMs)' output quality at the cost of diversity, yielding highly similar outputs across g

OptiWorld: Optimal Control for Video World Generation under Physical Constraints

arXiv:2606.00499v1 Announce Type: new Abstract: Video generation models are becoming a scalable form of world models, but they mainly generate plausible motion rather than proactively control or optim

Order within Chaos: Capturing Intrinsic Energy Anomalies for AI-Manipulated Image Forgery Localization

arXiv:2606.02178v1 Announce Type: cross Abstract: Recent advancements in generative AI have led to image editing models capable of producing realistic forgeries that evade traditional image forgery lo

OSCAR: Obstacle Survival Curves for Adaptive Robot Navigation

arXiv:2606.00990v1 Announce Type: new Abstract: A mobile robot following a graph of known routes can make costly navigation errors when a temporary obstacle blocks a critical edge: waiting too long be

safetyarxiv-cs-ro

PaCo-VLA: Passivity-Shielded Compliance Prior for Contact-Rich Vision-Language-Action Manipulation

arXiv:2606.00515v1 Announce Type: cross Abstract: Contact-rich manipulation demands both high-level semantic reasoning and the safe regulation of high-frequency contact dynamics. While Vision-Language

applicationsarxiv-cs-ai

PaCX-MAE: Physiology-Augmented Chest X-Ray Masked Autoencoder

arXiv:2606.01537v1 Announce Type: new Abstract: Clinical diagnosis often requires combining imaging with physiological measurements, yet deployed models typically operate on unimodal data. We present

Tutorials

PALTO: Physics-Informed Active Learning for Tri-Gate FinFET Design Optimization for Vertical Power Delivery

arXiv:2606.01265v1 Announce Type: cross Abstract: This paper demonstrates the effectiveness of machine learning-driven optimization for designing application-specific GaN tri-gate FinFETs in vertical

tutorialsarxiv-cs-ai

PaperVoyager : Building Interactive Web with Visual Language Models

model-releasesarxiv-cs-cl

arXiv:2603.22999v3 Announce Type: replace Abstract: Recent advances in visual language models have enabled autonomous agents for complex reasoning, tool use, and document understanding. However, exist

Parametric Social Identity Injection and Diversification in Public Opinion Simulation

arXiv:2603.16142v2 Announce Type: replace Abstract: Large language models (LLMs) have recently been adopted as synthetic agents for public opinion simulation, offering a promising alternative to costl

applicationsarxiv-cs-cl

PathAR: Structure-First Autoregressive Synthesis of Multimodal Pathology Images

arXiv:2606.01543v1 Announce Type: new Abstract: Data scarcity in multimodal pathology motivates unified generative models that synthesize modality-specific appearance while preserving anatomically coh

PathCRF: Ball-Free Soccer Event Detection via Possession Path Inference from Player Trajectories

arXiv:2602.12080v2 Announce Type: replace Abstract: Despite recent advances in AI, event data collection in soccer still relies heavily on labor-intensive manual annotation. Although prior work has ex

researcharxiv-cs-lg

PECKER: A Precisely Efficient Critical Knowledge Erasure Recipe For Machine Unlearning in Diffusion Models

arXiv:2604.05634v2 Announce Type: replace Abstract: Machine unlearning (MU) has become a critical technique for GenAI models' safe and compliant operation. While existing MU methods are effective, mos

Perturbation Effects on Accuracy and Fairness among Similar Individuals

arXiv:2404.01356v3 Announce Type: replace-cross Abstract: Deep neural networks are vulnerable to adversarial perturbations that can simultaneously degrade prediction robustness and individual fairness

Phoneme-Level Visual Speech Recognition via Point-Visual Fusion and Language Model Reconstruction

arXiv:2507.18863v2 Announce Type: replace-cross Abstract: Visual Automatic Speech Recognition (V-ASR) is a challenging task that involves interpreting spoken language solely from visual information, s

researcharxiv-cs-cl

PhyScene3D: Physically Consistent Interactive 3D Tabletop Scene Generation

arXiv:2606.01649v1 Announce Type: new Abstract: Generating physically consistent 3D tabletop scenes is a fundamental yet underexplored problem for interactive and generalist robotic learning. The chal

safetyarxiv-cs-cv

Physically-Constrained Mamba-SDE for Remaining Useful Life Prediction under Irregular Observations

arXiv:2606.01894v1 Announce Type: new Abstract: Accurate Remaining Useful Life prediction is critical for industrial predictive maintenance. However, real-world deployment is challenging due to the ir

Physics-Guided Attention in a Lightweight TCN for Efficient WiFi CSI-Based Human Activity Recognition

arXiv:2606.01834v1 Announce Type: cross Abstract: Human Action Recognition (HAR) using WiFi Channel State Information (CSI) has gained increasing attention due to its non-contact, low-cost, and privac

PINNOCHIO: Physics-Informed Neural Network for Coupled Hyperelastic Interface-Volume Simulation in Orthognathic Surgery

arXiv:2606.01572v1 Announce Type: cross Abstract: Predicting patient-specific facial soft-tissue deformation is critical for iterative orthognathic surgery planning. However, current computational met

Plan-R1: Safe and Feasible Trajectory Planning as Language Modeling

model-releasesarxiv-cs-cv

arXiv:2505.17659v4 Announce Type: replace-cross Abstract: Safe and feasible trajectory planning is critical for real-world autonomous driving systems. However, existing learning-based planners rely he

Agents

PLanAR: Planning-Language-Grounded Agentic Reasoning for Robot Manipulation

arXiv:2602.01662v4 Announce Type: replace Abstract: Recent advances in vision-language models (VLMs) have enabled increasing progress in real-world robot manipulation. However, long-horizon manipulati

agentsarxiv-cs-ro

Planar Symmetric Pattern Generation

arXiv:2606.02073v1 Announce Type: new Abstract: Generating objects with specific symmetries is essential in various real-world scenarios. However, adapting existing 2D continuous representations to en

applicationsarxiv-cs-lg

Agents

PlatonicNav: Unveiling Semantic Correspondence in Navigation with Platonic Topological Maps

arXiv:2606.01788v1 Announce Type: new Abstract: Embodied visual navigation, where an agent perceives a complex environment and acts to reach a goal from raw sensory input, underpins a wide range of ap

agentsarxiv-cs-cv

Polaris: Scaling Up Instruction-Guided Image Generation Towards Millions of Personalized Style Needs

arXiv:2606.01858v1 Announce Type: new Abstract: Users increasingly expect image generation models to quickly adapt to highly diverse and personalized requirements, such as producing images with distin

PolarMem: A Training-Free Polarized Latent Graph Memory for Verifiable Vision-Language Models

arXiv:2602.00415v2 Announce Type: replace Abstract: Memory is not merely a storage mechanism for intelligent systems, but a structure for organizing evidence and constraining belief. This is especiall

Policy and World Modeling Co-Training for Language Agents

arXiv:2606.02388v1 Announce Type: cross Abstract: Reinforcement learning (RL) improves large language model (LLM) agents by teaching them which actions lead to high rewards, but provides little superv

Pre-Deployment Robustness Stress Testing for CT Segmentation Systems Using Clinically Motivated Multi-Corruption Augmentation

arXiv:2606.00491v1 Announce Type: cross Abstract: Deep learning-based CT segmentation systems often achieve high accuracy on clean benchmark images, but their performance may degrade under heterogeneo

Hardware

Predicting Future Utility: Global Combinatorial Optimization for Task-Agnostic KV Cache Eviction

arXiv:2602.08585v2 Announce Type: replace-cross Abstract: Given the quadratic complexity of attention, KV cache eviction is vital to accelerate model inference. Current KV cache eviction methods typic

hardwarearxiv-cs-ai

Princeton365: A Diverse Dataset with Accurate Camera Pose

model-releasesarxiv-cs-cv

arXiv:2506.09035v2 Announce Type: replace Abstract: We introduce Princeton365, a large-scale diverse dataset of 365 videos with accurate camera pose. Our dataset bridges the gap between accuracy and d

Principle-Evolvable Scientific Discovery via Uncertainty Minimization

arXiv:2602.06448v2 Announce Type: replace-cross Abstract: Large Language Model (LLM)-based scientific agents have accelerated scientific discovery, yet they often suffer from significant inefficiencie

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

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

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

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

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

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

model-releasesarxiv-cs-lg

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

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

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

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

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

RAFT: Data Refinement and Adaptive Distillation for Domain Fine-Tuning with Alleviated Forgetting

arXiv:2606.00147v1 Announce Type: cross Abstract: Domain-specific supervised fine-tuning (SFT) often improves in-domain performance at the cost of degrading a model's general capabilities. We view thi

RAIGen: Rare Attribute Identification in Text-to-Image Generative Models

arXiv:2602.06806v2 Announce Type: replace Abstract: Text-to-image diffusion models achieve impressive generation quality but inherit and amplify training-data biases, skewing coverage of semantic attr

safetyarxiv-cs-cv

RankByGene: Gene-Guided Histopathology Representation Learning Through Cross-Modal Ranking Consistency

arXiv:2411.15076v3 Announce Type: replace-cross Abstract: Spatial transcriptomics (ST) provides essential spatial context by mapping gene expression within tissue, enabling detailed study of cellular

safetyarxiv-cs-cv

Agents

RDA: Reward Design Agent for Reinforcement Learning

arXiv:2606.01672v1 Announce Type: new Abstract: Reinforcement learning has enabled the acquisition of impressive robotic skills, but typically requires hand-crafted reward functions that are slow to d

agentsarxiv-cs-lg