All entries

Environment Parameter Gradient Theorem for Policy-Environment Co-Design in Reinforcement Learning

arXiv:2607.12590v1 Announce Type: cross Abstract: Reinforcement learning (RL) is traditionally concerned with learning a control policy for a fixed environment. In many engineering systems, however, t

Model Releases

Epistemic Stance Flexibility Probing: Measuring Prompt-Conditioned Register Shift in Large Language Models

DGX agent

arXiv:2607.12739v1 Announce Type: new Abstract: A language model may be asked either what experts believe about a contested claim or what it believes about the claim itself. A trustworthy conversation

model-releasesarxiv-cs-cl

15 Jul 2026

Evaluating Health Misinformation in Low-Resource Languages: Integrating Small Language Models with a Culturally-Sensitive Responsible NLP Framework (Bangla as a Case Study)

arXiv:2607.12336v1 Announce Type: cross Abstract: Artificial Intelligence (AI) technologies, while serving as a foundational enabler for modern social media and digital health services, exert a bivale

Evaluating Large Language Models on Misconceptions in Multi-Turn Medical Conversations

arXiv:2607.12884v1 Announce Type: new Abstract: Patients seeking medical information often ask questions that embed incorrect assumptions or misconceptions. In such cases, safe medical communication r

Evaluating Nonuniform Dependability Across Response Conditions: A Conditional Generalizability Framework Illustrated in Automated Essay Scoring

arXiv:2607.11981v1 Announce Type: cross Abstract: Aggregate reliability estimates can obscure heterogeneity in measurement-design burden across response conditions, so a single G- or D-study may misch

Applications

Evaluating Reliability in Machine Learning Models for Early Chronic Kidney Disease Prediction: A Systematic Review of Data Leakage and Predictor Stability

arXiv:2607.11963v1 Announce Type: cross Abstract: The early detection of Chronic Kidney Disease using machine learning has attracted significant interest in healthcare-related computer science. Despit

applicationsarxiv-cs-ai

Evidence-Grounded AI for Musculoskeletal Care

arXiv:2607.12527v1 Announce Type: new Abstract: Musculoskeletal diseases are among the leading causes of disability worldwide and create the greatest global need for rehabilitation. Because recovery,

Evidence-Grounded Verified Agentic Reasoning: A Path Toward Eliminating LLM Hallucination in Empirical Inference via Tool-Attested Kernel Proofs

arXiv:2607.12650v1 Announce Type: cross Abstract: Tool access alone does not make LLM empirical reasoning governable: accepted outputs need not descend from attested evidence, and accepted deductions

agentsarxiv-cs-ai

Evidence Recomposition and Predictive Context Residualization for Visual Attribution in Multimodal Large Language Models

arXiv:2509.22415v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) have achieved strong vision-language performance, yet their token-level visual evidence remains diffi

EvoGraph-R1: Self-Evolving Multimodal Knowledge Hypergraphs for Agentic Retrieval

arXiv:2607.12764v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) has emerged as a critical paradigm for grounding Multimodal Large Language Models (MLLMs) in external knowledge. Re

agentsarxiv-cs-cv

Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning

arXiv:2509.24372v3 Announce Type: replace-cross Abstract: Fine-tuning large language models (LLMs) for downstream tasks is an essential stage of modern AI deployment. Reinforcement learning (RL) has e

EVOQUANT: Self-Evolving Verifier-Guided Strategy Optimization for Robust Quantitative Trading

arXiv:2607.12455v1 Announce Type: new Abstract: Quantitative strategy optimization remains largely manual, requiring domain experts to identify weak signals, tune risk-control rules, and repeatedly va

Exact and Calibrated Diffusion Reconstruction for Digital Breast Tomosynthesis

arXiv:2607.12937v1 Announce Type: cross Abstract: Limited-angle digital breast tomosynthesis (DBT) reconstructs a volume from a few low-dose projections over a narrow arc. At a representative nine-vie

researcharxiv-cs-cv

Exact and Certified Data Shapley for Weighted k-Nearest-Neighbor Regression and Soft-Label Prediction

arXiv:2607.11956v1 Announce Type: cross Abstract: Data Shapley is the standard principled answer to which training points are worth what, and its k-nearest-neighbor (KNN) specialization is the version

Excited for our first general model Inkling -- open weights, 975B, natively multimodal (text, image, audio). Available on Tinker, HuggingFac…

researchsoumith-chintala--x

Excited for our first general model Inkling -- open weights, 975B, natively multimodal (text, image, audio). Available on Tinker, HuggingFace and partners. It is yours to personalize and use openly. I

ExLlamaV3 v1.0.0 - Major Performance Upgrades

After over a year in development, ExLlamaV3 has had its first production release. Turboderp has been pulling 10 hour days with Fable to bring us this massive batch of improvements. Check out detailed

local-air-localllama

Expert Knowledge-driven Reinforcement Learning for Autonomous Racing via Trajectory Guidance and Dynamics Constraints

arXiv:2603.05842v2 Announce Type: replace Abstract: Reinforcement learning has demonstrated significant potential in the field of autonomous driving. However, it suffers from defects such as training

safetyarxiv-cs-ro

Explainable-by-Design Audio Deepfake Detection via Wiener-Hopf Linear Prediction

arXiv:2607.12584v1 Announce Type: cross Abstract: The rapid advancement of synthetic speech generation methods has made audio deepfake detection a critical challenge in multimedia forensics. While rec

Exploring Zero-Shot Foundation Models for Multivariate Time Series Anomaly Detection

arXiv:2607.12454v1 Announce Type: new Abstract: Multivariate Time Series Anomaly Detection (MTSAD) is essential for reliability and safety in domains such as industrial process monitoring and financia

ExToken: Structured Exploration for Efficient Vision-Language-Action Reinforcement Fine-tuning

arXiv:2607.12931v1 Announce Type: new Abstract: Reinforcement Learning (RL) has demonstrated significant potential for improving Vision-Language-Action (VLA) models on complex manipulation tasks. Howe

safetyarxiv-cs-ro

Extractable Memorization From First Principles

arXiv:2607.12649v1 Announce Type: cross Abstract: Recent work on extractable memorization in LLMs suffers from two contrasting validity problems. Some studies overstate extraction, e.g., relying on se

Extracting information from millions of documents at scale used to take an insane number of human hours. Even with recent OCR + document AI …

Extracting information from millions of documents at scale used to take an insane number of human hours. Even with recent OCR + document AI tech, humans would still have to spend a lot of time careful

agentsjerry-liu--x

ExtraGS: Enhancing Endoscopic View Extrapolation via Diffusion-Guided 3D Gaussian Splatting

arXiv:2607.12785v1 Announce Type: new Abstract: Robot-assisted minimally invasive surgery (MIS) critically depends on reliable endoscopic perception for navigation and safety. However, conventional en

safetyarxiv-cs-cv

Applications

FAIR GraphRAG: A Retrieval-Augmented Generation Approach for Semantic Data Analysis

arXiv:2607.11464v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) addresses the limitations of Large Language Models (LLMs) when providing responses to domain-specific questions.

applicationsarxiv-cs-ai

FairCoder: Probing LLM Bias in High-Stakes Decision Making via Coding Tasks

arXiv:2501.05396v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in high-stakes decisions such as hiring and college admissions, making their social bias a critic

Tutorials

Falsifying Causal Graphs With Outlier Events

arXiv:2607.12145v1 Announce Type: cross Abstract: True causal relationships are rarely known, and inferring causal graphs from data is hard. A fundamental challenge is how to assess whether a given ca

tutorialsarxiv-cs-lg

Fast and Accurate Image Restoration and Generation with Rank Enhanced Linear Attention

arXiv:2505.16157v2 Announce Type: replace Abstract: Transformer-based models have made remarkable progress in image restoration (IR) tasks. However, the quadratic complexity of self-attention in Trans

researcharxiv-cs-cv

Filtering-out poor-quality images for data preparation

arXiv:2607.12352v1 Announce Type: new Abstract: Filtering noise is a fundamental part of data preparation that enhances image quality for applications such as object segmentation, detection, and recog

agentsarxiv-cs-cv

Fin-Analyst at FinMMEval 2026 Task 3: A Live Hybrid Trading Agent with LLM Specialists and Rule-Based Signals

arXiv:2607.12233v1 Announce Type: cross Abstract: Large language model (LLM) trading agents show promising performance in equity markets, yet remain narrowly focused on US equities with little evidenc

agentsarxiv-cs-ai

Fine-Tuned Multi-Agent Framework for Detecting OCEAN in Life Narratives

arXiv:2607.12215v1 Announce Type: new Abstract: Accurately assessing personality from text is challenging because traits are latent, context-dependent, and often subtly expressed across long narrative

agentsarxiv-cs-cl

FinResearchBench II: A Deep Research Benchmark with Consensus-Derived Gold Rubrics for Distinguishing Financial Report Quality

arXiv:2607.12252v1 Announce Type: new Abstract: Deep research agents are increasingly used to produce long-form financial reports, yet large-scale evaluation remains bottlenecked by the need for human

First, do NOHARM: a medical safety benchmark and randomized study of physician and AI teaming on clinical consultations

arXiv:2512.01241v4 Announce Type: replace-cross Abstract: Large language models (LLMs) and medical AI tools are routinely used by physicians and patients for medical advice, yet their clinical safety

Tutorials

Fisher Rank Inflation: A Spectral Signature of Memorization under Label Noise

arXiv:2607.12438v1 Announce Type: new Abstract: Deep networks trained with label noise often learn clean structure before memorizing corrupted labels. We show that this transition leaves a spectral si

tutorialsarxiv-cs-lg

Hardware

FlashDiff: Efficient Regional Execution and Scheduling for Diffusion Model Serving

arXiv:2607.12121v1 Announce Type: cross Abstract: Diffusion models have become the central backbone for modern image, video, and audio generation, but their efficient service remains a challenge. Unli

hardwarearxiv-cs-lg

Flatness-Preserving Residual Learning for Real-Time Tight Quadrotor Formation Flight

arXiv:2607.12275v1 Announce Type: new Abstract: Quadrotors flying in tight formations are severely affected by turbulent aerodynamic interactions, such as downwash, that can cause catastrophic collisi

researcharxiv-cs-ro

FlowWAM: Optical Flow as a Unified Action Representation for World Action Models

arXiv:2607.13017v1 Announce Type: cross Abstract: World Action Models (WAMs) are able to leverage pretrained video generators for both world modeling and action prediction. However, directly leveragin

safetyarxiv-cs-cv

Follow the Latent Roadmap: Navigating Revocable Decoding for Diffusion LLMs with Anchor Tokens

arXiv:2606.16847v3 Announce Type: replace-cross Abstract: Diffusion Large Language Models (dLLMs) offer a promising avenue for parallel generation but face a trade-off between decoding speed and quali

local-aiarxiv-cs-ai

Forgetful Attention: A Trainable Support-Vector Memory with Certified Selection and Exact Unlearning

arXiv:2607.12204v1 Announce Type: new Abstract: Attention can be viewed as an online learner over context, yet existing test-time memories cannot certify that dropping a token leaves outputs unchanged

Form, Not Content? A Preregistered, Placebo-Controlled Evaluation of Learned Error-Conditioned Self-Repair Through Prompts and Weights in Frozen Small Code Models

arXiv:2607.12962v1 Announce Type: cross Abstract: Frozen small code LLMs are deployed locally, yet the information guiding a retry after a failed attempt is still measured without placebo controls in

local-aiarxiv-cs-ai

FormalAnalyticGeo: A Neural-Symbolic Based Framework for Multimodal Analytic Geometry Problem Generation

arXiv:2607.12982v1 Announce Type: new Abstract: Math reasoning has achieved significant progress with the rapid advancement of Multimodal Large Language Models (MLLMs), however analytic geometry remai

FoundationGeo: Learning Spatial Pixel-Wise Fields for Monocular Metric Geometry

arXiv:2607.11588v2 Announce Type: replace Abstract: We present FoundationGeo, a two-stage framework that explicitly bridges relative and metric prediction via spatial calibration and principled data d

local-aiarxiv-cs-cv

From Critic to Confidence: PPO for Language-Based Quantitative Prediction with Confidence Estimation

arXiv:2607.12687v1 Announce Type: cross Abstract: LLMs can perform language-based quantitative prediction from unstructured inputs, but remain susceptible to hallucinations and overconfident errors, m

From Geometric Recovery to Causal Validation: A Reproducible Audit of Sparse Autoencoder Features, from Superposition Geometry to Causal Inertness

arXiv:2607.12166v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are the standard for decomposing superposed neural representations into interpretable features, and evaluation relies predomi

safetyarxiv-cs-lg

From Hindsight to Foresight: Self-Encouraged Hindsight Distillation for Knowledge-based Visual Question Answering

arXiv:2511.11132v4 Announce Type: replace Abstract: Knowledge-based Visual Question Answering (KBVQA) necessitates external knowledge incorporation beyond cross-modal understanding. Existing KBVQA met

researcharxiv-cs-cv

From Many to Meaningful: Feature-Guided Zero-Shot Chronic Kidney Disease Screening Using Large Language Models

arXiv:2607.12260v1 Announce Type: new Abstract: Early screening of chronic kidney disease (CKD) is essential for preventing irreversible progression; however, many machine learning (ML)-based screenin

From Observation to Insight: Mechanistic World Models and the Quest for Autonomous Discovery

arXiv:2607.12474v1 Announce Type: new Abstract: Recent advances in foundation models have transformed AI for Science, enabling remarkably accurate predictive performance across domains ranging from pr

agentsarxiv-cs-ai

From Preimage Search To Source-Grounded Feature Inversion

arXiv:2607.12526v1 Announce Type: new Abstract: Interpreting a neural network requires understanding what its internal features extract from a particular input. Feature inversion seeks to express a se

local-aiarxiv-cs-lg

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data

arXiv:2607.12175v1 Announce Type: cross Abstract: X-ray tomography enables nondestructive characterization of material microstructures, while advances in micro-CT imaging have accelerated volumetric d