Search: “papers”

Measuring What Matters: A Unified Evaluation Framework for GNN Explainability

arXiv:2607.04600v1 Announce Type: new Abstract: Graph eXplainable AI (G-XAI) is increasingly important for making Graph Neural Networks interpretable and accountable. While a growing number of explain

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Medi-Gemma: A Hybrid Clinical Decision Support System Integrating Deterministic EMR Analytics and Retrieval-Augmented Generation

DGX agent

arXiv:2607.04907v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) in high-stakes clinical settings remains limited by structural hallucinations, weak deterministic reasoning over

model-releasesarxiv-cs-ai

7 Jul 2026

Memory-Efficient FastText: A Comprehensive Approach Using Double-Array Trie Structures and Mark-Compact Memory Management

model-releasesarxiv-cs-cl

arXiv:2506.01254v2 Announce Type: replace Abstract: FastText remains a practical choice for industrial word representation because it can synthesize vectors for out-of-vocabulary words from character

MemPose: Category-level Object Pose Estimation with Memory

arXiv:2607.04930v1 Announce Type: cross Abstract: In the pursuit of robust and generalizable category-level object pose estimation, most existing methods adopt parametric formulations that learn effec

MetaMax: Improved Open-Set Deep Neural Networks via Weibull Calibration

arXiv:2211.10872v2 Announce Type: replace Abstract: Open-set recognition refers to the problem in which classes that were not seen during training appear at inference time. This requires the ability t

Modular Foundation Models for Time-Series Perception in Digital Twins

model-releasesarxiv-cs-lg

arXiv:2607.03585v1 Announce Type: new Abstract: Engineering Digital Twins and Prognostics and Health Management (PHM) systems rely on robust perception modules to extract actionable information from h

Motion Estimation Techniques for Volumetric Video Attribute Compression

arXiv:2607.03576v1 Announce Type: cross Abstract: Point cloud compression relies on techniques to compress both geometry and attributes. Motion-based approaches for dynamic solid point cloud geometry

MPSelectTune: Prompt-type Selection for Fine-tuning improves Concept Unlearning in LLMs

arXiv:2607.03932v1 Announce Type: cross Abstract: LLMs can be conveniently adapted to a diverse set of tasks, e.g, prediction, question-answering tasks, etc, using appropriate prompts with few-shot ex

Multi-Way Representation Alignment

arXiv:2602.06205v2 Announce Type: replace-cross Abstract: The Platonic Representation Hypothesis suggests that independently trained neural networks converge to increasingly similar latent spaces. How

safetyarxiv-cs-ai

NABLA: Neighborhood Adaptive Block-Level Attention

arXiv:2507.13546v2 Announce Type: replace Abstract: Recent progress in transformer-based architectures has demonstrated remarkable success in video generation tasks. However, the quadratic complexity

Tutorials

Neuro-symbolic Weak Supervision: Theory and Semantics

arXiv:2503.18509v2 Announce Type: replace Abstract: Weak supervision enables machine learning models to learn from limited or noisy labels, but it introduces challenges in reliability and semantic cla

tutorialsarxiv-cs-ai

Next-Gen Sponsored Search: Crafting the Perfect Query with Inventory-Aware RAG (InvAwr-RAG) Based GenAI

arXiv:2607.03880v1 Announce Type: cross Abstract: Sponsored search plays a crucial role in e-commerce revenue generation, where advertisers strategically bid on keywords to capture the attention of us

Non-Asymptotic Error Bounds for SMC with Biased Proposals: Application to Conditional Diffusion Sampling

arXiv:2607.04780v1 Announce Type: cross Abstract: Sequential Monte Carlo (SMC) methods are a natural tool for post-hoc conditioning of pretrained generative models, but in many applications the mutati

safetyarxiv-cs-lg

NouveauVoice: Generating Novel Pseudo Speakers for Voice Anonymization

arXiv:2607.03985v1 Announce Type: cross Abstract: Advanced neural technologies in speech synthesis and voice conversion (VC) have introduced severe risks to personal privacy, necessitating robust Spea

OmniOpt: Taxonomy, Geometry, and Benchmarking of Modern Optimizers

arXiv:2607.04033v1 Announce Type: cross Abstract: Optimizer selection for large-scale model training has become a system-level design decision constrained jointly by compute, memory, tuning budget, an

On Preserving Geometrical Invariance for Superpixel Image Classification using Graph Transformer

arXiv:2607.04262v1 Announce Type: new Abstract: Convolutional Neural Network (CNN) and Vision Transformer (ViT) for image classification exploit a dense grid of pixels containing redundant information

On Regularization via Early Stopping for Least Squares Regression

arXiv:2406.04425v2 Announce Type: replace Abstract: A fundamental problem in machine learning is understanding the effect of early stopping on the parameters obtained and the generalization capabiliti

One Prompt, Many Sounds: Modeling Listener Variability in LLM-Based Equalization

arXiv:2601.09448v3 Announce Type: replace-cross Abstract: Conventional audio equalization is a static process that requires manual and cumbersome adjustments to adapt to changing listening contexts (e

Open-Attribute Person Retrieval: Finding People Through Distinctive and Novel Attributes

arXiv:2508.01389v3 Announce Type: replace Abstract: Person retrieval in surveillance videos often depends on attributes described by witnesses or operators. However, the most useful cues in practice a

safetyarxiv-cs-cv

Agents

Optimal-Agent-Selection: State-Aware Routing Framework for Efficient Multi-Agent Collaboration

arXiv:2511.02200v2 Announce Type: replace Abstract: The emergence of multi-agent systems powered by large language models (LLMs) has unlocked new frontiers in complex task-solving, enabling diverse ag

agentsarxiv-cs-ai

Panorama: Fast-Track Nearest Neighbors

arXiv:2510.00566v4 Announce Type: replace-cross Abstract: Approximate Nearest-Neighbor Search (ANNS) pipelines for high-dimensional neural embeddings spend the bulk of their query time in candidate ve

PCA of probability measures: Sparse and Dense sampling regimes

arXiv:2602.02190v2 Announce Type: replace-cross Abstract: A common approach to perform PCA on probability measures is to embed them into a Hilbert space where standard functional PCA techniques apply.

pFedNavi: Structure-Aware Personalized Federated Vision-Language Navigation for Embodied AI

arXiv:2602.14401v2 Announce Type: replace-cross Abstract: Vision-Language Navigation VLN requires large-scale trajectory instruction data from private indoor environments, raising significant privacy

PixWorld: Unifying 3D Scene Generation and Reconstruction in Pixel Space

arXiv:2607.05373v1 Announce Type: new Abstract: 3D reconstruction and generation are commonly tackled by separate paradigms: pixel-based regression for reconstruction, and latent diffusion for generat

PLGSA-Transformer: Periocular Landmark-Guided Attention with Occlusion-Adaptive Cosine Thresholding for Cross-Modal Masked and Unmasked Face Recognition

arXiv:2607.03581v1 Announce Type: cross Abstract: The widespread adoption of facial masks, accelerated by COVID-19 and mandated in security-sensitive settings, has exposed limitations of conventional

applicationsarxiv-cs-ai

Poisson-Gamma Modeling of Inter-Relational Dependencies in Dynamic Knowledge Graphs

model-releasesarxiv-cs-lg

arXiv:2607.02872v1 Announce Type: new Abstract: Dynamic knowledge graphs are ubiquitous in today's AI applications, as we represent molecular structures, social relationships, and language information

Policy Improvement with Style-Specific Demonstrations

arXiv:2506.16995v4 Announce Type: replace Abstract: Proficient game agents with diverse play styles enrich the gaming experience and enhance the replay value of games. However, recent advancements in

safetyarxiv-cs-ai

Pooling-Based Context Modeling for Convolution-Free Deep Image Prior

arXiv:2607.02952v1 Announce Type: cross Abstract: Convolutional Neural Networks (CNNs) achieve strong denoising performance by exploiting spatial context from neighboring pixels. Deep Image Prior (DIP

PraMem: Practice-derived Experiential Memory for Long-horizon Behavior Prediction

arXiv:2607.02881v1 Announce Type: new Abstract: Long-horizon behavior prediction aims to infer a user's next action based on a lengthy historical sequence, playing a crucial role in artificial intelli

researcharxiv-cs-cl

Privacy-Preserving Industrial Ergonomics: mmWave-Based Automated REBA Scoring and Pose Estimation

arXiv:2607.02611v1 Announce Type: new Abstract: Work-related Musculoskeletal Disorders (WMSDs) require continuous ergonomic assessments. While Rapid Entire Body Assessment (REBA) is a gold-standard ob

Progress- and Reliability-Oriented Group Policy Optimization for Agentic Reinforcement Learning

arXiv:2607.04242v1 Announce Type: new Abstract: Group-based reinforcement learning (RL) has become an effective paradigm for improving large language model agents on long-horizon interactive tasks. To

safetyarxiv-cs-ai

Progressive Refinement: An Iterative Pseudo-Labeling Approach for Mandarin-English Code-Switching ASR

arXiv:2607.05224v1 Announce Type: new Abstract: Code-switching (CS), alternating languages within the same utterance, poses significant challenges for automatic speech recognition (ASR) due to limited

researcharxiv-cs-cl

ProLaViT: Learning Progressive Latent Visual Thoughts in Structured Latent Space

arXiv:2607.02907v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress but still struggle with complex visual reasoning tasks requiring multi-step

researcharxiv-cs-cl

Agents

PromptPET: Privacy-Utility Optimized Prompt Obfuscation

arXiv:2607.02932v1 Announce Type: cross Abstract: Privacy is an important challenge when users interact with AI chatbots, since users may share sensitive information, explicitly or implicitly, and AI

agentsarxiv-cs-ai

PuzzleMoE: Efficient Compression of Large Mixture-of-Experts Models via Sparse Expert Merging and Bit-packed inference

arXiv:2511.04805v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models have shown strong potential in scaling language models efficiently by activating only a small subset of expert

QSVideo: Query-Conditioned Semantic Temporal Retrieval for Video Understanding

arXiv:2607.04559v1 Announce Type: new Abstract: The performance of vision-language models (VLMs) in video understanding declines with increasing video duration, as video moments unrelated to the query

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QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting

arXiv:2607.02632v1 Announce Type: cross Abstract: Time-series forecasting supports decisions in finance, en-ergy, transportation, public health, and industrial monitoring. Recent foundation models imp

applicationsarxiv-cs-ai

Quantum Kolmogorov--Arnold representation theorem for continuous unitary-valued maps

arXiv:2607.03187v1 Announce Type: cross Abstract: The classical Kolmogorov--Arnold representation theorem states that any continuous multivariate function can be exactly decomposed into a finite compo

Rank-Order N-of-M Codes for Sparse Distributed Memory: Disentangling Representation and Learning Effects in Noise Robustness Against Contemporary Neuromorphic Architectures

arXiv:2607.02967v1 Announce Type: new Abstract: Large language models remain limited as continual learning systems, motivating renewed interest in Sparse Distributed Memory (SDM) as an explicit online

REAL-OW: Rehearsal-free Open World Object Detection with Low-Rank Adaptation and Dual-Stage Objectness Modeling

arXiv:2607.03004v1 Announce Type: new Abstract: Open-World Object Detection (OWOD) requires detectors to identify previously unseen objects as unknown and incrementally incorporate them into the set o

applicationsarxiv-cs-cv

Reconstructing Rational Functions on Finite Abelian Groups with Higher Autocorrelations

arXiv:2503.21022v2 Announce Type: replace Abstract: The higher-order autocorrelations of integer-valued or rational-valued functions on finite Abelian groups appear naturally in X-ray crystallography,

Reconstruction-Anchored Diffusion Model for Text-to-Motion Generation

model-releasesarxiv-cs-cv

arXiv:2601.14788v2 Announce Type: replace Abstract: Diffusion models have seen widespread adoption for text-driven human motion generation and related tasks due to their impressive generative capabili

Reduced-Order Models: The Mother of World Models

arXiv:2607.03198v1 Announce Type: new Abstract: World models -- compressed latent representations of an environment that support action-conditioned prediction and planning -- are typically presented a

Reducing the Complexity of Deep Learning Models for EEG Analysis on Wearable Devices

arXiv:2606.12742v3 Announce Type: replace Abstract: Wearable healthcare devices are the fastest-growing Internet of Things (IoT) sector. Many automated healthcare services rely on two crucial biologic

Relevance-Based Embeddings: Lightweight Candidate Retrieval via Heavy-Ranker Calls

arXiv:2607.03515v1 Announce Type: cross Abstract: In many machine learning applications, the most relevant items for a query should be efficiently retrieved. The relevance function is usually an expen

applicationsarxiv-cs-lg

Reliability and Identifiability in Persona-Trained Monte Carlo: Variance Decomposition, Stability Bounds, and the Identifiability of Heterogeneous News Reaction

arXiv:2607.04627v1 Announce Type: new Abstract: Persona-Trained Monte Carlo (PTMC) estimates distributions of market-outcome functionals by repeatedly simulating limit-order-book interaction among K n

safetyarxiv-cs-lg

Repurposing CLIP to Localize at Pixel Level

arXiv:2607.05253v1 Announce Type: new Abstract: Large-scale Vision-Language Models like CLIP have demonstrated impressive open-set localization capabilities at the image level. However, adapting this

RES-DARE: Failure-Aware Expert Adaptation and Rollback-Safe Self-Repair for Intrusion Detection

model-releasesarxiv-cs-lg

arXiv:2607.02687v1 Announce Type: cross Abstract: Intrusion detection systems are often trained under static benchmark conditions, although deployed network environments are affected by traffic drift,