Search: “index”

Impute-EM: Native Mixed-State Diffusion Models for Heterogeneous Data Imputation

arXiv:2609.15284v1 Announce Type: new Abstract: Missing values are ubiquitous in heterogeneous data mining, where numerical, categorical, and binary variables often coexist. Many imputation methods, e

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IROH: Insightful Ranking Of Humor using Multi-Stage Hybrid Retrieval with Rationale-Distilled LLM Judges for JOKER 2026 Track Task 1 English

DGX agent

arXiv:2609.15618v1 Announce Type: cross Abstract: Our team, VANGUARD, presents IROH (Insightful Ranking of Humor), a three-stage retrieval system for JOKER Task 1 English at CLEF 2026, achieving first

model-releasesarxiv-cs-cl

15 Sept 2026

Medical Knowledge Simplification for Patients in the Era of LLMs: A Case Study on Diabetes

arXiv:2609.15129v1 Announce Type: new Abstract: Complex medical information is often difficult for patients to understand, making effective medical knowledge simplification essential for improving pat

applicationsarxiv-cs-ai

Mixture-of-Experts Language Models Can Be Strong and Efficient Retrievers

model-releasesarxiv-cs-cl

arXiv:2609.13486v1 Announce Type: cross Abstract: Recent work has shown that fine-tuning decoder-only large language models (LLMs) for retrieval yields strong first-stage retrievers, with effectivenes

MoME: Mixture-of-Memory Embeddings for Context-Aware Sparse Lookup

model-releasesarxiv-cs-ai

arXiv:2609.15126v1 Announce Type: cross Abstract: Scaling large language models efficiently has motivated sparse capacity mechanisms such as Mixture-of-Experts and, more recently, conditional memory:

MoVT: Video-Augmented Motion Tokenizer for Text-to-Motion Generation

arXiv:2609.14965v1 Announce Type: new Abstract: Text-driven 3D human motion generation models face significant challenges in responding to diverse and unconstrained textual prompts, primarily due to t

applicationsarxiv-cs-cv

Navigating Sparse Evidence: Agentic Visual RAG via Explicit Context Selection and Consolidation

arXiv:2609.15800v1 Announce Type: new Abstract: Visual Retrieval-Augmented Generation (VRAG) empowers models to navigate and answer queries about visually rich documents by retrieving relevant page im

POLARIS: Training-Free Audio Fingerprinting with Saliency-Based Landmarks and Delaunay Grouping

arXiv:2609.14820v1 Announce Type: cross Abstract: This work presents POLARIS, a training-free audio fingerprinting system that selects landmarks from a locally normalized saliency field and groups the

Query-Oblivious Coresets for Softmax Attention: Improved Bounds and Efficient Constructions

model-releasesarxiv-cs-cl

arXiv:2609.06327v2 Announce Type: replace-cross Abstract: A query-oblivious coreset for a softmax-attention head is a subset of the key-value pairs whose attention output is within arepsilon of the fu

Scalable partial information decomposition for symptom networks via supervised embeddings

arXiv:2609.13203v1 Announce Type: new Abstract: Pairwise relationships among mental-health symptoms are routinely summarised asscalar edge weights, which cannot express whether two symptoms carry over

Task-Based CT Protocol Optimization Using Reinforcement Learning and Virtual Imaging Trials

arXiv:2609.13309v1 Announce Type: cross Abstract: Protocol optimization in computed tomography (CT) aims to improve diagnostic image quality while reducing radiation dose, but the interdependence of a

Touch2Trace: Tactile-Driven Imitation Learning for Dexterous Cable Tracing

arXiv:2609.15921v1 Announce Type: new Abstract: Dexterous manipulation of deformable objects demands continuous fingertip-level regulation of pressure, friction, and incipient slip. We study one of th

safetyarxiv-cs-ro

Transfer Learning for Socioeconomic Estimation in Forced-Displacement Settings

arXiv:2609.15773v1 Announce Type: cross Abstract: Progress in inclusive household surveys has strengthened socioeconomic evidence for forcibly displaced populations, providing indispensable benchmarks

researcharxiv-cs-ai

Where Should Language Sit in a Multimodal Model? Lessons from What Language Does to Human Perception and Cognition

arXiv:2609.07474v2 Announce Type: replace Abstract: Language models compute over tokens: language is their input, their output, and increasingly their internal representation. Whether language should

safetyarxiv-cs-cl

AIM: A Privacy-Aware Interoperable Memory Framework for Multi-Agent Multi-User LLM Systems

arXiv:2609.12320v1 Announce Type: cross Abstract: Traditional large language models (LLMs) are scoped to individual user sessions, limiting their knowledge to a single conversation and preventing them

Creating an Atomic User Model for Personality-Aware Large Language Model Interaction

arXiv:2609.12086v1 Announce Type: cross Abstract: Assistants built on large language models are expected to write as their user would, and the dominant approach is single-channel: preferences summaris

researcharxiv-cs-cl

Detecting and Explaining Fake News Short Videos with Multimodal Content and Real-World Evidence

arXiv:2609.12678v1 Announce Type: new Abstract: Short-video platforms have become a primary news source for the public, which has also enabled the widespread dissemination of fake news videos. We stud

applicationsarxiv-cs-cv

Quantile-based Loss Filtering for Outlier-Robust Stochastic Gradient Descent

arXiv:2609.13040v1 Announce Type: new Abstract: We study loss-based filtering for finite-sum optimization with a subset of corrupted component functions whose gradients may be highly unreliable. Motiv

Hardware

Characterizing Job Power Elasticity for Power-Flexible AI Training

arXiv:2609.11542v1 Announce Type: new Abstract: Large language model (LLM) training is among the fastest-growing sources of electricity demand in modern data centers, and power availability is a prima

hardwarearxiv-cs-ai

12 Sept 2026

Finishing the Task Is Not Enough: Evaluating Agent Resilience and Considerate Participation under Accumulating Challenge

arXiv:2609.10724v1 Announce Type: new Abstract: Sustained deployment of generative AI agents requires more than isolated task success. Agents must remain useful across repeated interactions, changing

12 Sept 2026

MOSAIC: Query-Aware Exploration Policy Adaptation for GraphRAG

model-releasesarxiv-cs-ai

arXiv:2609.11065v1 Announce Type: new Abstract: Graph Retrieval-Augmented Generation (GraphRAG) can connect evidence distributed across a corpus graph, but most systems use largely shared exploration

12 Sept 2026

Detectable Only Where It Is Confounded: What Verified Duplication Counts Say About Membership Evidence in Language Models

arXiv:2609.10830v1 Announce Type: new Abstract: When a language model finds a sentence unusually cheap to predict, it is tempting to conclude that the sentence was in its training data. Almost every p

researcharxiv-cs-cl

DriftNet: A Dual-Head Trajectory Transformer for Detecting and Localizing Prompt Injection in LLM Agents

arXiv:2609.10892v1 Announce Type: cross Abstract: When an indirect prompt injection succeeds against an LLM agent, the compromise is visible in the agent's own behavior: a benign prefix of tool calls,

Prevalence Determines Precision:Silent Contamination in Detector-Defined Datasets

arXiv:2609.11449v1 Announce Type: new Abstract: Many ML datasets are constructed by running a detector, heuristic, or model over candidate pools; accepted items become labels. Dataset precision is the

Self-Supervised Cardiac Phase Detection via Single-Parameter Latent Orbits

arXiv:2609.11650v1 Announce Type: new Abstract: Accurate identification of end-diastole (ED) and end-systole (ES) in echocardiography underpins the quantification of ventricular function, yet manual s

Test time training enhances in-context learning of nonlinear functions

arXiv:2509.25741v3 Announce Type: replace-cross Abstract: Test-time training (TTT) enhances model performance by explicitly updating designated parameters prior to each prediction to adapt to the test

The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement

arXiv:2609.11873v1 Announce Type: cross Abstract: Recursive self-improvement (RSI) enables AI systems to turn experience and feedback into persistent changes that improve both their capabilities and t

researcharxiv-cs-cl

The Oligarch Barely Steers Model Collapse in Multi-Model Ecosystems

arXiv:2609.11146v1 Announce Type: cross Abstract: AI-generated text is flowing back into the training corpora of the next generation of models. Recursive training on it drives model collapse, and rece

safetyarxiv-cs-cl

What Should an Agent Forget? Separating What Is Stored from What Is Used

arXiv:2609.10263v1 Announce Type: new Abstract: Persistent language agents need stored experience to remain available across time, while each answer requires evidence suited to a particular question.

Beyond Conventional Federated Learning via High-Order Regularization

arXiv:2609.09904v1 Announce Type: new Abstract: Federated clients that perform several local optimization steps can return parameter displacements with widely different magnitudes. The quadratic regul

Beyond One-Shot Expansion: Contrastive Evidence Exploration for Multi-Hop Retrieval

arXiv:2609.07050v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) critically depends on retrieving the evidence necessary for effective reasoning. However, this remains particularly

researcharxiv-cs-ai

CHIMERA Challenge Task 2 and 3: Response Subtypes Classification and Progression Survival Prediction in Bladder Cancer Patients using Multimodal Datasets

arXiv:2609.09510v1 Announce Type: cross Abstract: High-risk non-muscle-invasive bladder cancer (HR-NMIBC) carries substantial risks of recurrence and progression, while current clinical risk stratific

FastE: Readout-Triggered Token Compression for LLM Embedding Inference

arXiv:2609.08407v1 Announce Type: new Abstract: In this study, we identify depth-dependent prefix redundancy in final-readout LLM embedding models, notably across representative backbones including Qw

Geometric organization of olfactory descriptor data in the Poincare disk

arXiv:2609.09573v1 Announce Type: cross Abstract: Odor quality is commonly represented using high dimensional descriptor profiles, yet their low dimensional organization remains unclear. We investigat

Mapping the Emerging Social Science of Large Language Models

arXiv:2609.07598v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly shape communication, learning, work, creativity, and decision-making, yet social-science research on these d

MemForest: Efficient Agent Memory Management via EventTree Partitioning and Progressive Merging

arXiv:2609.08273v1 Announce Type: new Abstract: Agent memory systems have demonstrated significant potential in long-term dialogue, personalized assistants, and video understanding. However, continuou

Multi-Functional Embedding Models for Funder Name Disambiguation in Scientific Publication Records

model-releasesarxiv-cs-cl

arXiv:2609.09984v1 Announce Type: new Abstract: Understanding the historical allocation and distribution of research funding advances our knowledge of how scientific research is supported across field

PAGR: Proof-Carrying Algebraic-Geometric Retrieval: A Quiver-, Provenance-, and Sheaf-Theoretic Framework for Grounded LLM Retrieval

arXiv:2609.06127v1 Announce Type: cross Abstract: Retrieval-augmented generation is usually formulated as a statistical information-retrieval problem. Graph-based variants add relational structure, bu

researcharxiv-cs-ai

Predicting Estimated Times of Restoration for Electrical Outages Using Longitudinal Tabular Transformers

arXiv:2505.00225v2 Announce Type: replace Abstract: Utilities publish Estimated Times of Restoration (ETRs) for customer-facing storm outages, and their accuracy governs whether customers can make sou

PRIMUS: Identity, Governance, and Verification for Multi-Agent Federations

arXiv:2609.07910v1 Announce Type: new Abstract: Multi-agent federations need governance that answers three questions under adversarial conditions: who participated (identity), did they conform (enforc

The Living Library: Transforming Archival Collections into Conversational Knowledge Systems -- Lessons from the Theodore Roosevelt Presidential Library

arXiv:2609.09368v1 Announce Type: new Abstract: We present the Living Library, an end-to-end framework for transforming fragmented digital archives into governed, conversational, in-person exhibit exp

When Does Low-Bit Quantization Preserve the Decisions of Vector Search?

arXiv:2609.09854v1 Announce Type: cross Abstract: Low-bit quantization can achieve high recall on some vector representations and fail sharply on others, while average distortion and global rank corre

XAI-Refine: An Automated Explanation-Knowledge Loop for Brain-Age Prediction

arXiv:2609.09388v1 Announce Type: new Abstract: Brain-age prediction models are commonly evaluated by predictive accuracy, yet accurate predictions alone do not establish that a model relies on reprod

safetyarxiv-cs-lg

Cadence: Error-Bounded Lossy Compression of Demand Time Series with a Time-Series Foundation Model

arXiv:2609.06008v1 Announce Type: cross Abstract: We present Cadence, an error-bounded lossy compressor for numeric time series pairing a 330M-parameter time-series foundation model (Google TimesFM-3)

EigenLI: Spectral Approximations to Late Interaction

arXiv:2609.07561v1 Announce Type: cross Abstract: Late-interaction models such as ColBERT achieve strong effectiveness by representing each document with many token-level vectors, but this expressivit

Gaussian Linear Functional Manifold Method for Massive Point Cloud Data

arXiv:2609.05744v1 Announce Type: new Abstract: Reconstructing continuous terrain manifolds from massive, unstructured airborne LiDAR point clouds remains challenging in complex Wildland-Urban Interfa

Hi-FLoop: Hierarchical State-Feedback Loops for Multi-Timescale World Modeling

arXiv:2609.08796v1 Announce Type: new Abstract: Multi-agent traffic simulation seeks diverse, coordinated, and physically realistic futures from maps and observed history. Long-horizon closed-loop gen

agentsarxiv-cs-cv

Not Just Oversmoothing: Detecting the Echo Chamber Effect in Graph Neural Networks

arXiv:2609.06521v1 Announce Type: new Abstract: Oversmoothing is a well-known failure mode of Graph Neural Networks (GNNs). However, most existing diagnostics rely on global aggregation measures that

applicationsarxiv-cs-lg