Search: “research”

PhysScene: A Scene Graph Dataset for Scientific Visual Reasoning in Physics Experiments

arXiv:2606.09368v1 Announce Type: cross Abstract: Scene Graphs (SGs) provide structured representations of visual scenes by modeling objects and their pairwise relationships. Despite recent progress,

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Pointwise Complexity for Gaussian Fields: Upper Envelopes, Algorithmic Lower Bounds, and Separation

DGX agent

arXiv:2606.07931v1 Announce Type: cross Abstract: We prove a variance-aware pointwise majorizing-measure theorem for centered Gaussian processes. Classical generic chaining characterizes the scalar qu

researcharxiv-cs-lg

9 Jun 2026

PolyBuild: An End-to-End Method for Polygonal Building Contour Extraction from High-Resolution Remote Sensing Images

arXiv:2606.08920v1 Announce Type: cross Abstract: Extracting building polygon contours from high-resolution remote sensing images is a fundamental task for various mapping applications. However, the p

Post-AGI Economies: Superposition and the Second Fundamental Theorem of Welfare Economics

arXiv:2606.08267v1 Announce Type: cross Abstract: The classical Second Welfare Theorem decentralizes any Pareto efficient allocation through prices and transfers under convexity and regularity. In pos

Post-Rejection Follow-up Sampling: A Methodology for Counterfactual Outcome Measurement in Algorithmic DEX Trading

arXiv:2606.08228v1 Announce Type: cross Abstract: Algorithmic trading systems on decentralised exchanges (DEXs) reject most candidate tokens they evaluate. The counterfactual outcome of rejected candi

Powering the Future of AI: Navigating the Trade-offs for Europe's Energy Transition and Net-Zero Goals

arXiv:2606.09617v1 Announce Type: cross Abstract: The rapid expansion of AI globally has led to the proliferation of energy-intensive hyperscale data centres (DCs), making them as a structurally chall

Predictive Coding with Bayesian Priors via Proximal Gradients

arXiv:2606.08374v1 Announce Type: cross Abstract: We recast predictive coding as continuous-time proximal gradient descent applied to a regularized maximum-a-posteriori (MAP) objective. We study first

Preserving Plasticity in Continual Learning via Dynamical Isometry

arXiv:2606.09762v1 Announce Type: cross Abstract: Continual training of deep neural networks under non-stationarity often leads to a progressive loss of plasticity, eventually limiting further learnin

Priors Persist Through Suppression: A Stroop Paradigm for Lexical Override

arXiv:2606.07555v1 Announce Type: cross Abstract: Glossaries, technical specifications, and system prompts routinely ask language models to use familiar words in unfamiliar ways. When this works, the

Proposal Refinement for Few-Shot Object Detection

arXiv:2606.09245v1 Announce Type: cross Abstract: Few-shot object detection has gained widely attention in recent years. Some excellent algorithms have been proposed to handle this task. However, most

Provably Efficient Personalized Multi-Objective Bandits with Proactive Conversational Queries

arXiv:2606.08410v1 Announce Type: cross Abstract: Personalized decision-making in multi-objective bandits requires learning user-specific trade-offs among competing objectives. Since arm utility depen

Q-Delta: Beyond Key-Value Associative State Evolution

arXiv:2606.08804v1 Announce Type: new Abstract: Linear attention reformulates sequence modeling as recurrent state evolution, enabling efficient linear-time inference. Under the key-value associative

Quantum-Enhanced Similarity Measures for Polarimetric Materials Classification

arXiv:2606.07766v1 Announce Type: cross Abstract: We present a quantum--classical hybrid pipeline for polarimetric material classification that casts this as a point-matching problem. Voxel cubes, con

Quantum Global Variational Learning for Quantum Error Correction

arXiv:2606.08592v1 Announce Type: new Abstract: Efficient quantum error correction is essential for the advancement of quantum computing. We propose a quantum neural network with a global structure th

Quantum latent distributions in deep generative models

arXiv:2508.19857v3 Announce Type: replace Abstract: Many successful families of generative models leverage a low-dimensional latent distribution that is mapped to a data distribution. Though simple la

Quantum Maximum Likelihood Prediction via Hilbert Space Embeddings

arXiv:2602.18364v2 Announce Type: replace-cross Abstract: Maximum likelihood prediction (MLP) is a core task at the heart of modern large language models. Here, we study a quantum version of this task

Query Lens: Interpreting Sparse Key-Value Features with Indirect Effects

arXiv:2606.07617v1 Announce Type: cross Abstract: While sparse autoencoders provide features more interpretable than individual neurons, reliably characterizing them remains challenging. We propose Qu

Querying Counterfactuals on Tissue Graphs with Supervised Disentanglement

arXiv:2606.08493v1 Announce Type: cross Abstract: extit{Tissue graph counterfactuals} ask how a cell's expression would change under altered spatial neighbor contexts. Such queries are central to pred

QuoVLA: Quotient Space for Vision-Language-Action Models

arXiv:2605.24890v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models commonly adapt pretrained Vision-Language Models (VLMs) to robot control by mapping visual observations and lang

RACT: Retrieval Augmented Column-Table Learning and Prediction for Multi-Table Schema Matching

arXiv:2606.07843v1 Announce Type: cross Abstract: Schema matching, a critical task for integrating data from diverse sources, seeks to identify correspondences between columns across different schemas

RadOT-Eval: Auditable Structured-Evidence Transport for Radiology Report Evaluation

arXiv:2606.08769v1 Announce Type: cross Abstract: Automatic evaluation is critical for high-stakes text generation, where errors often involve omitted findings, hallucinated content, polarity reversal

RAM: Reachability Across Morphologies

arXiv:2606.09108v1 Announce Type: cross Abstract: Many stages of the robotic lifecycle, from morphology synthesis to operation, rely fundamentally on the reachable workspace. However, current methods

Rank Intervals for Leaderboards: A Hierarchical Framework for Model Evaluation

arXiv:2606.08679v1 Announce Type: cross Abstract: Pretrained models are often evaluated on multi-task leaderboards to measure their applicability in diverse contexts. However, current methods for aggr

RAPID: Layer-Wise Redundancy-Aware Pruning and Importance-Driven Token Merging for Efficient ViT

arXiv:2606.08156v1 Announce Type: cross Abstract: Vision Transformers (ViTs) achieve strong performance but suffer from high computational costs due to quadratic self-attention complexity. Although to

Reachability and asymptotics of Gaussian Transformer dynamics

arXiv:2606.07600v1 Announce Type: cross Abstract: We formulate data propagation through the Transformer, the machine learning architecture powering large language models, as a nonlinear control system

REACT 2026: The Fourth Multiple Appropriate Facial Reaction Generation Challenge: Personalised MAFRG and Appropriate EEG Reaction Prediction

arXiv:2606.07935v1 Announce Type: new Abstract: In dyadic interactions, various human facial reactions could be appropriate for responding to each human speaker behaviour. Following the successful org

Reasoning Arena: Trace Tournaments When Verifiable Rewards Fall Short

arXiv:2606.09380v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a leading paradigm for improving the reasoning ability of large language models throu

Reconstructing Synthetic SDO/AIA 193 A EUV Images from He I 10830 A Observations with Diffusion Model Translator

arXiv:2606.08652v1 Announce Type: cross Abstract: Routine full-disk EUV imaging has been available only since the modern era, such as SOHO and SDO. To extend EUV coronal context into earlier periods,

Report the Floor: A Training-Free Conformal Interval Is a Mandatory Baseline for Probabilistic Time-Series Forecasting

arXiv:2606.09473v1 Announce Type: cross Abstract: Probabilistic forecasters are increasingly learned, yet the baselines they are compared against are often weak or omitted. We show that the simplest p

Rethinking 3D Shape Generation: Diffusion over Superquadrics

arXiv:2606.08957v1 Announce Type: new Abstract: Diffusion models have advanced 3D shape generation, yet most methods still denoise in high-cardinality spaces (e.g., voxel/SDF grids, meshes, or point c

RetroReasoner: A Reasoning LLM for Strategic Retrosynthesis Prediction

arXiv:2603.12666v2 Announce Type: replace-cross Abstract: Retrosynthesis prediction aims to identify reactants that can synthesize a given product molecule. Although molecular large language models (L

Rewrite to Translate, Translate to Reward: Reinforcement Learning for Source Rewriting in Machine Translation

arXiv:2606.08011v1 Announce Type: cross Abstract: Although directly prompting off-the-shelf Large Language Models (LLMs) to generate meaning-preserving source rewrites can effectively enhance Machine

Robust In-Context Reinforcement Learning Under Reward Poisoning Attacks

arXiv:2506.06891v3 Announce Type: replace Abstract: We study the corruption-robustness of in-context reinforcement learning (ICRL), focusing on the Decision-Pretrained Transformer (DPT, Lee et al., 20

Robust Random Graph Matching in Dense Graphs via an Approximate Message Passing Type Algorithm

arXiv:2412.16457v3 Announce Type: replace-cross Abstract: In this paper, we focus on the matching recovery problem between a pair of correlated Gaussian Wigner matrices with a latent vertex correspond

SAEExplainer: Interpreting SAE Features with Activation-Guided Preference Optimization

arXiv:2606.08496v1 Announce Type: cross Abstract: Although Sparse Autoencoders (SAEs) have mitigated the opacity of large language models (LLMs) by decomposing dense representations into sparse featur

SafeECGMatch: Calibration-Aware Joint Frequency and Time Space Semi-Supervised Learning for Open-Set ECG Classification

arXiv:2606.08037v1 Announce Type: cross Abstract: Electrocardiogram (ECG) classification models often suffer from severe label scarcity, making semi-supervised learning (SSL) an attractive strategy fo

SAGE: Shape-Adapting Gated Experts for Adaptive Histopathology Image Segmentation

arXiv:2511.18493v4 Announce Type: replace-cross Abstract: The significant variability in cell size and shape continues to pose a major obstacle in computer-assisted cancer detection on gigapixel Whole

Scaling Decision-Focused Learning to Large Problems with Lagrangian Decomposition

arXiv:2606.08797v1 Announce Type: cross Abstract: Decision-focused learning has shown great promise for addressing predict-then-optimize problems, particularly in the presence of under-specified model

Scaling Participation in Modular AI Systems

arXiv:2606.07812v1 Announce Type: new Abstract: Humanity is a mosaic of multifaceted talents and needs, and any truly intelligent AI must reflect that richness. Yet the LLMs used by all are built by t

Safety

SciTrace: Trajectory-Aware Safety Reasoning for Scientific Discovery Agents

arXiv:2606.08234v1 Announce Type: new Abstract: LLM-based scientific agents have shown strong capacity for autonomous research, yet their safety layers remain structurally divorced from core reasoning

safetyarxiv-cs-ai

Securing Self-supervised Data Curation for Foundation Models Robustness

arXiv:2606.09511v1 Announce Type: new Abstract: Self-supervised data curation provides a pathway to scaling and improving the generalization capabilities of machine learning models. By leveraging self

Seeing is Believing: Aligning Prompt Rewriting with Visual Anchors for Text-to-Image Generation

arXiv:2606.08492v1 Announce Type: cross Abstract: Despite the impressive capabilities of text-to-image (T2I) models, an intent-generation gap often persists due to the brevity and ambiguity of user pr

Segment-level Tree Search for Long Meeting Document Summarization

arXiv:2606.08445v1 Announce Type: cross Abstract: Meeting documents are challenging to summarize due to their length and complex conversational structure. Existing approaches typically adopt multi-sta

Segmentation-Assisted Brain MRI Synthesis with Cross-Image Multi-Contrast Feature Memory Bank Retrieval Augmentation

arXiv:2606.08421v1 Announce Type: new Abstract: Multi-contrast brain MRI provide complementary soft-tissue characteristics that aid in the screening and diagnosis of diseases. However, limited scannin

Self-supervised Learning Matters: A Simple Ensemble Solution for Micro-Gesture Recognition

arXiv:2606.09261v1 Announce Type: new Abstract: In this paper, we present XInsight Lab's solution to the micro-gesture classification track of the 4th MiGA Challenge at IJCAI 2026, in which our soluti

Self-Supervised Vision Transformers for CBCT-Based Detection of Temporomandibular Joint Osteoarthritis

arXiv:2606.08364v1 Announce Type: cross Abstract: Temporomandibular joint osteoarthritis (TMJ OA) is a prevalent degenerative condition whose osseous changes are often subtle on cone-beam CT (CBCT), m

Semantic Cache Distillation: Efficient State Transfer via Reuse and Selective Patching

arXiv:2606.07684v1 Announce Type: cross Abstract: Disaggregated serving alleviates memory bottlenecks in Large Language Model (LLM) inference but creates a severe communication bottleneck: transmittin

Set-Based Transformer for Atmospheric Compensation in Standoff LWIR Hyperspectral Imaging

arXiv:2606.08324v1 Announce Type: cross Abstract: Passive long-wave infrared (LWIR) hyperspectral imaging under a standoff geometry depends on atmospheric absorption and emission, as well as reflected