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PRA-RAG: Provably Robust Aggregation in Retrieval-Augmented Generation against Retrieval Corruption

arXiv:2607.00012v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by incorporating external knowledge, effectively mitigating their inherent

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Predicting Lethal Outcome (Cause) And Understanding Key Biomarkers Linked With Acute Myocardial Infarction Using Deep Artificial Neural Network And Ensemble Of Machine Learning Methodologies

DGX agent

arXiv:2607.00472v1 Announce Type: cross Abstract: Cardiovascular disease is still one of the main causes of death around the world. Acute myocardial infarction (MI), or heart attack, claims millions o

researcharxiv-cs-ai

2 Jul 2026

[Preprint] Dynamic Modeling, Gait Synthesis, and Control of a Novel Subsurface Bore Propagator

arXiv:2607.00569v1 Announce Type: new Abstract: In this article, we present dynamic modeling, gait synthesis, and feedback control design for a modular novel subsurface robot, designed for human-free

researcharxiv-cs-ro

PRISM-VO: Scale-Aware Visual Odometry Using Photometric Plenoptic Bundle Adjustment

arXiv:2607.00176v1 Announce Type: new Abstract: We introduce PRISM-VO, a novel pure optimization-based sparse photometric visual odometry framework for focused plenoptic cameras. The core of PRISM-VO

Program Manager (RSI Lab) https://sakana.ai/careers/program-manager-rsi-lab/

Sakana AI is hiring a Program Manager for its RSI (Research and Systems Integration) Lab, as posted on their careers page. The role likely involves managing research initiatives, coordinating between

researchdavid-ha--x

Progressive Pose-Guided 4D Animal Reconstruction from Monocular Video

arXiv:2607.00157v1 Announce Type: new Abstract: Reconstructing 4D animals from monocular videos is challenging due to large inter-species variation, complex articulations, and the lack of reliable tem

Prototype Memory-Guided Training-Free Anomaly Classification and Localization in Prenatal Ultrasound

arXiv:2607.00744v1 Announce Type: cross Abstract: Prenatal anomaly classification and localization is of critical importance for fetal health and pregnancy management. Although ultrasound (US) is the

QCA: Query- and Content-Aware Keyframe Selection for Long Video Understanding

arXiv:2607.00983v1 Announce Type: new Abstract: Video understanding is often plagued by severe temporal redundancy, where processing dense frame sequences is both semantically inefficient and computat

Quadratic Programming Approach for Nash Equilibrium Computation in Multiplayer Imperfect-Information Games

arXiv:2509.25618v2 Announce Type: replace-cross Abstract: There has been significant recent progress in algorithms for approximation of Nash equilibrium in large two-player zero-sum imperfect-informat

Quantitative Understanding of PDF Fits and their Uncertainties

arXiv:2512.24116v3 Announce Type: replace-cross Abstract: Parton Distribution Functions (PDFs) play a central role in describing experimental data at colliders and provide insight into the structure o

Reading Order Inference for Complex Document Layouts

arXiv:2607.01018v1 Announce Type: cross Abstract: Reading order inference remains a critical bottleneck in the digitization of complex historical manuscripts, where pages contain multiple spatially in

Recursively Enumerably Representable Classes and Computable Versions of the Fundamental Theorem of Statistical Learning

arXiv:2511.02644v2 Announce Type: replace Abstract: We study computable probably approximately correct (CPAC) learning, where learners are required to be computable functions. It had been previously o

Relation-Centric Open-Vocabulary 3D Gaussian Segmentation

arXiv:2607.01140v1 Announce Type: new Abstract: Open-vocabulary 3D Gaussian segmentation is challenging because it requires language understanding for diverse queries and accurate separation of Gaussi

Representation as a Bottleneck for Mechanistic Interpretability: The Manifestation Unit Protocol

arXiv:2607.00089v1 Announce Type: new Abstract: Mechanistic interpretability has produced a rich inventory of component-level analyses that characterise what neural-network components encode and how t

Residual Context Diffusion Language Models

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Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to purely autoregressive language models because they can decode multiple tokens in parallel. However, state-of-the-art

Rethinking Robust Adversarial Concept Erasure in Diffusion Models

arXiv:2510.27285v4 Announce Type: replace Abstract: Concept erasure methods aim to remove specific unsafe target concepts in diffusion models while preserving image generation utility. To address the

Rethinking Visual Privacy: A Compositional Privacy Risk Framework for Severity Assessment with VLMs

arXiv:2603.21573v2 Announce Type: replace Abstract: Existing visual privacy benchmarks largely treat privacy as a binary property, labeling images as private or non-private based on visible sensitive

Reward function compression facilitates goal-dependent reinforcement learning

arXiv:2509.06810v3 Announce Type: replace-cross Abstract: Humans can uniquely assign value to novel, abstract outcomes to support reinforcement learning. However, this flexibility is cognitively costl

Root Cause Analysis of Outliers in Unknown Cyclic Graphs

arXiv:2510.06995v2 Announce Type: replace-cross Abstract: We study the propagation of outliers in cyclic causal graphs with linear structural equations, tracing them back to one or several 'root cause

Rosetta: Composable Native Multimodal Pretraining

arXiv:2607.00293v1 Announce Type: cross Abstract: Achieving true artificial general intelligence requires foundation models capable of integrating new modalities without forgetting prior knowledge. Ho

researcharxiv-cs-cl

Sample Complexities of Estimating Gumbel--Max Watermark Proportions with and without Reduction to Pivotal Statistics

arXiv:2607.00224v1 Announce Type: cross Abstract: Watermarking promises a statistical trace of large language model (LLM) use, but real documents, after editing or paraphrasing, rarely arrive as purel

Scaling Up Thermodynamic AI Models

arXiv:2607.00170v1 Announce Type: cross Abstract: Thermodynamic computing devices based on the Ising model show great promise for low-power AI inference and edge computing, but scalable methods for tr

scDataset: Scalable Data Loading for Deep Learning on Large-Scale Single-Cell Omics

arXiv:2506.01883v3 Announce Type: replace-cross Abstract: Training deep learning models on single-cell datasets with hundreds of millions of cells requires loading data from disk, as these datasets ex

Search-Based Spatiotemporal and Multi-Robot Motion Planning on Graphs of Space-Time Convex Sets

arXiv:2607.00444v1 Announce Type: cross Abstract: Spatiotemporal motion planning, especially in multi-robot settings, requires robots to reason about collision-free regions that change over time, whic

SEFORA: Student Essays with Feedback Corpus and LLM Feedback Evaluation Framework

arXiv:2607.00274v1 Announce Type: cross Abstract: Effective writing feedback is among the strongest drivers of student learning, yet producing it at scale is labor-intensive. LLMs offer a natural path

SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization

arXiv:2604.06817v2 Announce Type: replace Abstract: We present SemEval-2026 Task 9, a shared task on online polarization detection, covering 22 languages and comprising over 110K annotated instances.

researcharxiv-cs-cl

SemiScope: Disentangling Classifier Tuning and Joint Optimization in Semi-Supervised Security Classification

arXiv:2607.00113v1 Announce Type: new Abstract: Background. Labeled data for security classification is scarce. Semi-supervised learning (SSL) propagates labels from a small labeled pool to larger unl

SFDATrack: Generalized Source-Free Domain Adaptive Tracking Under Adverse Weather Conditions

arXiv:2607.00369v1 Announce Type: new Abstract: Domain adaptive visual object tracking under adverse weather conditions has garnered significant attention in recent years. Despite the impressive perfo

Since Trump took office: * Elon net worth is 980B (+500B) * Donald Trump's family ~10B, up about 7B * Top 15 billionaires: up 33% And US…

Since Trump took office: * Elon net worth is 980B (+500B) * Donald Trump's family ~10B, up about 7B * Top 15 billionaires: up 33% And USAID was cut 6 billion, resulting in hundreds of thousands of or

researchyann-lecun--x

SkipGS: Post-Densification Backward Skipping for Efficient 3DGS Training

arXiv:2603.08997v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) achieves real-time novel-view synthesis by optimizing millions of anisotropic Gaussians, yet its training remains expen

SLIM-RL: Risk-Budgeted Random-Masking RL for Diffusion LLMs Without Trajectory Slicing

arXiv:2607.00208v1 Announce Type: cross Abstract: Reinforcement learning for diffusion large language models (dLLMs) has largely moved to trajectory-aware methods. The current state of the art, TraceR

Slope-Guided Mamba and Angular-Refined Transformer for Light Field Super-Resolution

arXiv:2607.00965v1 Announce Type: new Abstract: Light Field Super-Resolution (LFSR) necessitates accurate modeling of spatial-angular correlations while preserving intrinsic 4D ray coherence. However,

Solution space path planning for supporting en-route air traffic control

arXiv:2607.00064v1 Announce Type: new Abstract: As technology advances, many path-planning algorithms have been proposed for Air Traffic Management, yet their operational adoption in tactical control

SONIC: Spectral Optimization of Noise for Inpainting with Consistency

arXiv:2511.19985v3 Announce Type: replace Abstract: We propose a novel training-free method for inpainting with off-the-shelf text-to-image models. While guidance-based methods in theory allow generic

SPECSIA: Stylization Dataset for Novel-View Enhancement in Drawing-based 3D Animation

arXiv:2607.00525v1 Announce Type: new Abstract: Generating animation from a single 2D drawing is challenging because the output must preserve character appearance while remaining plausible and tempora

Spectral Geometry and Bosonic-Bloch Probes: Explorations in Quantum Learning

arXiv:2607.00063v1 Announce Type: cross Abstract: This paper studies how spectral geometry emerges in quantum learning models and how it can be diagnosed with physically grounded probes. In graph-regu

Spectroscopy Analysis with Machine Learning Regression for the Quantification of Carbon and Nitrogen Contents in Inceptisol and Oxisol Soil Types: Comparing Different Preprocessing and Validation methods as well as Feature Importance

arXiv:2607.00834v1 Announce Type: new Abstract: Near-Infrared (NIR) spectroscopy has emerged as a promising alternative to traditional soil analysis methods, offering advantages such as speed, low cos

Spotted: Location-informed Reidentification of Hyenas and Leopards in Camera Trap Surveys

arXiv:2607.00804v1 Announce Type: new Abstract: Animal re-identification (ReID) in camera-trap surveys remains challenging due to low image quality, strong variation in illumination and viewpoint, and

Stateful Token Reduction for Long-Video Hybrid VLMs

arXiv:2603.00198v2 Announce Type: replace-cross Abstract: Token reduction accelerates long-video vision--language models (VLMs), but existing methods target Transformers, where reduction is treated as

Stop Pretending Social Robots Are Inevitable

arXiv:2607.00142v1 Announce Type: new Abstract: This paper takes issue with the recent themes of both the RO-MAN and the HRI conferences for their portrayal of a future human-robot society as inevitab

researcharxiv-cs-ro

Structural Pattern Mining in Inka Khipus: Unsupervised Clustering, Provenance Classification, and a Computational Validation of the Santa Valley Match

arXiv:2607.00185v1 Announce Type: new Abstract: Khipus--knotted cord devices--were the primary recording medium of the Inka Empire (c. 1400-1532 CE), yet their system remains undeciphered. We present

researcharxiv-cs-cl

Synergistic Perception-Reasoning Governance: Grounding Medical MLLMs with Verifiable Anatomical Evidence

arXiv:2607.00060v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) show strong promise for clinical VQA and radiology report generation, yet inference-time hallucinations still u

Task-Relevant Representation Decoupling for Visual Reinforcement Learning Generalization

arXiv:2607.00796v1 Announce Type: new Abstract: Visual Reinforcement Learning (VRL) has achieved considerable success in solving control tasks. However, generalizing learned policies to new environmen

Technical Report: Asynchronous Distributed Trajectory Estimation of Multi-Robot Systems

arXiv:2607.01106v1 Announce Type: new Abstract: Distributed trajectory estimation arises in many applications across robotics, but existing implementations typically do not consider asynchrony in agen

researcharxiv-cs-ro

The Binary Tree Mechanism is Optimal for Approximate Differentially Private Continual Counting

arXiv:2607.00876v1 Announce Type: cross Abstract: Private continual counting is a fundamental problem in differential privacy: given a binary stream of length n, where each 1 corresponds to the contri

The last paragraph of @AnneApplebaum’s piece on what patriotism means ahead of our 250th Independence Day. https://www.theatlantic.com/ideas…

The last paragraph of @AnneApplebaum’s piece on what patriotism means ahead of our 250th Independence Day. https://www.theatlantic.com/ideas/2026/07/america-250-july-4-idea/687749/?utm_source=twitter&

researchyann-lecun--x

The Narrative Strategy of Sam Altman on CNBC today… Some notes from discussing this ‘we will give America 5% of OpenAI’ idea… 1 - Strategica…

The Narrative Strategy of Sam Altman on CNBC today… Some notes from discussing this ‘we will give America 5% of OpenAI’ idea… 1 - Strategically it makes sense for OpenAI to Invite This Matrix-multipli

researchyann-lecun--x

The State-Prediction Separation Hypothesis

arXiv:2607.01218v1 Announce Type: cross Abstract: Transformers use the same forward computation stream to both predict the next token and store useful state for future token predictions. We formulate