research

Rapid LoRA Aggregation for Wireless Channel Adaptation in Open-Set Radio Frequency Fingerprinting

arXiv:2604.12834v1 Announce Type: cross Abstract: Radio frequency fingerprints (RFFs) enable secure wireless authentication but struggle in open-set scenarios with unknown devices and varying channels

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ReefMapGS: Enabling Large-Scale Underwater Reconstruction by Closing the Loop Between Multimodal SLAM and Gaussian Splatting

DGX agent

arXiv:2604.11992v1 Announce Type: cross Abstract: 3D Gaussian Splatting is a powerful visual representation, providing high-quality and efficient 3D scene reconstruction, but it is crucially dependent

researcharxiv-cs-cv

15 Apr 2026

Refined Differentially Private Linear Regression via Extension of a Free Lunch Result

arXiv:2604.11820v1 Announce Type: cross Abstract: As data-privacy regulations tighten and statistical models are increasingly deployed on sensitive human-sourced data, privacy-preserving linear regres

Replicable Reinforcement Learning with Linear Function Approximation

arXiv:2509.08660v3 Announce Type: replace Abstract: Replication of experimental results has been a challenge faced by many scientific disciplines, including the field of machine learning. Recent work

Representation geometry shapes task performance in vision-language modeling for CT enterography

arXiv:2604.13021v1 Announce Type: cross Abstract: Computed tomography (CT) enterography is a primary imaging modality for assessing inflammatory bowel disease (IBD), yet the representational choices t

Representing 3D Faces with Learnable B-Spline Volumes

arXiv:2604.12894v1 Announce Type: new Abstract: We present CUBE (Control-based Unified B-spline Encoding), a new geometric representation for human faces that combines B-spline volumes with learned fe

Representing expertise accelerates learning from pedagogical interaction data

arXiv:2604.12195v1 Announce Type: new Abstract: Work in cognitive science and artificial intelligence has suggested that exposing learning agents to traces of interaction between multiple individuals

ResBM: Residual Bottleneck Models for Low-Bandwidth Pipeline Parallelism

arXiv:2604.11947v1 Announce Type: cross Abstract: Unlocking large-scale low-bandwidth decentralized training has the potential to utilize otherwise untapped compute resources. In centralized settings,

Retrievals Can Be Detrimental: Unveiling the Backdoor Vulnerability of Retrieval-Augmented Diffusion Models

arXiv:2501.13340v4 Announce Type: replace Abstract: Diffusion models (DMs) have recently demonstrated remarkable generation capability. However, their training generally requires huge computational re

Robotic Nanoparticle Synthesis via Solution-based Processes

arXiv:2604.12169v1 Announce Type: new Abstract: We present a screw geometry-based manipulation planning framework for the robotic automation of solution-based synthesis, exemplified through the prepar

researcharxiv-cs-ro

Robust gene prioritization for Dietary Restriction via Fast-mRMR Feature Selection techniques

arXiv:2511.21211v3 Announce Type: replace Abstract: Gene prioritization (identifying genes potentially associated with a biological process) is increasingly tackled with Artificial Intelligence. Howev

Robust Reasoning and Learning with Brain-Inspired Representations under Hardware-Induced Nonlinearities

arXiv:2604.12079v1 Announce Type: cross Abstract: Traditional machine learning depends on high-precision arithmetic and near-ideal hardware assumptions, which is increasingly challenged by variability

RoleMAG: Learning Neighbor Roles in Multimodal Graphs

arXiv:2604.12271v1 Announce Type: new Abstract: Multimodal attributed graphs (MAGs) combine multimodal node attributes with structured relations. However, existing methods usually perform shared messa

ROSE: An Intent-Centered Evaluation Metric for NL2SQL

arXiv:2604.12988v1 Announce Type: cross Abstract: Execution Accuracy (EX), the widely used metric for evaluating the effectiveness of Natural Language to SQL (NL2SQL) solutions, is becoming increasing

RSGMamba: Reliability-Aware Self-Gated State Space Model for Multimodal Semantic Segmentation

arXiv:2604.12319v1 Announce Type: new Abstract: Multimodal semantic segmentation has emerged as a powerful paradigm for enhancing scene understanding by leveraging complementary information from multi

Scaling Exposes the Trigger: Input-Level Backdoor Detection in Text-to-Image Diffusion Models via Cross-Attention Scaling

arXiv:2604.12446v1 Announce Type: cross Abstract: Text-to-image (T2I) diffusion models have achieved remarkable success in image synthesis, but their reliance on large-scale data and open ecosystems i

Scaling In-Context Segmentation with Hierarchical Supervision

arXiv:2604.12752v1 Announce Type: new Abstract: In-context learning (ICL) enables medical image segmentation models to adapt to new anatomical structures from limited examples, reducing the clinical a

SceneCritic: A Symbolic Evaluator for 3D Indoor Scene Synthesis

arXiv:2604.13035v1 Announce Type: cross Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) increasingly generate indoor scenes through intermediate structures such as layouts and

SCRIPT: A Subcharacter Compositional Representation Injection Module for Korean Pre-Trained Language Models

arXiv:2604.12377v1 Announce Type: cross Abstract: Korean is a morphologically rich language with a featural writing system in which each character is systematically composed of subcharacter units know

Seeking Critique on Research Approach to Open Set Recognition (Novelty Detection) [R]

researchr-machinelearning

This is a community discussion post on the r/MachineLearning subreddit where a researcher shares their proposed methodology for tackling Open Set Recognition (OSR) and/or novelty detection, inviting p

Should There be a Teacher In-the-Loop? A Study of Generative AI Personalized Tasks Middle School

arXiv:2602.15876v1 Announce Type: cross Abstract: Adapting instruction to the fine-grained needs of individual students is a powerful application of recent advances in large language models. These gen

Software Engineer (Research and Development) https://sakana.ai/careers/#software-engineer-research-and-development

Sakana AI is hiring a Software Engineer focused on Research and Development, as shared by David Ha (known as hardmaru on X), who is a co-founder of the Tokyo-based AI research company. The role likely

researchdavid-ha--x

SOLARIS: Speculative Offloading of Latent-bAsed Representation for Inference Scaling

arXiv:2604.12110v1 Announce Type: new Abstract: Recent advances in recommendation scaling laws have led to foundation models of unprecedented complexity. While these models offer superior performance,

SpanKey: Dynamic Key Space Conditioning for Neural Network Access Control

arXiv:2604.12254v1 Announce Type: cross Abstract: SpanKey is a lightweight way to gate inference without encrypting weights or chasing leaderboard accuracy on gated inference. The idea is to condition

Speaker effects in language comprehension: An integrative model of language and speaker processing

arXiv:2412.07238v3 Announce Type: replace Abstract: The identity of a speaker influences language comprehension through modulating perception and expectation. This review explores speaker effects and

SpecBound: Adaptive Bounded Self-Speculation with Layer-wise Confidence Calibration

arXiv:2604.12247v1 Announce Type: cross Abstract: Speculative decoding has emerged as a promising approach to accelerate autoregressive inference in large language models (LLMs). Self-draft methods, w

Stress Detection Using Wearable Physiological and Sociometric Sensors

arXiv:2604.12746v1 Announce Type: new Abstract: Stress remains a significant social problem for individuals in modern societies. This paper presents a machine learning approach for the automatic detec

Subcritical Signal Propagation at Initialization in Normalization-Free Transformers

arXiv:2604.11890v1 Announce Type: new Abstract: We study signal propagation at initialization in transformers through the averaged partial Jacobian norm (APJN), a measure of gradient amplification acr

Synthetic POMDPs to Challenge Memory-Augmented RL: Memory Demand Structure Modeling

arXiv:2508.04282v3 Announce Type: replace Abstract: Recent benchmarks for memory-augmented reinforcement learning (RL) have introduced partially observable Markov decision process (POMDP) environments

Technical Report -- A Context-Sensitive Multi-Level Similarity Framework for First-Order Logic Arguments: An Axiomatic Study

arXiv:2604.12534v1 Announce Type: new Abstract: Similarity in formal argumentation has recently gained attention due to its significance in problems such as argument aggregation in semantics and enthy

Temporal Flattening in LLM-Generated Text: Comparing Human and LLM Writing Trajectories

arXiv:2604.12097v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in daily applications, from content generation to code writing, where each interaction treats the mod

The Download: NASA’s nuclear spacecraft and unveiling our AI 10

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. NASA is building the first nuclear reactor-powered interplanet

researchmit-tech-review

The Effect of Document Selection on Query-focused Text Analysis

arXiv:2604.12099v1 Announce Type: cross Abstract: Analyses of document collections often require selecting what data to analyze, as not all documents are relevant to a particular research question and

The Enforcement and Feasibility of Hate Speech Moderation on Twitter

arXiv:2604.12289v1 Announce Type: cross Abstract: Online hate speech is associated with substantial social harms, yet it remains unclear how consistently platforms enforce hate speech policies or whet

The Linear Centroids Hypothesis: How Deep Network Features Represent Data

arXiv:2604.11962v1 Announce Type: new Abstract: Identifying and understanding the features that a deep network (DN) extracts from its inputs to produce its outputs is a focal point of interpretability

The Non-Optimality of Scientific Knowledge: Path Dependence, Lock-In, and The Local Minimum Trap

arXiv:2604.11828v1 Announce Type: new Abstract: Science is widely regarded as humanity's most reliable method for uncovering truths about the natural world. Yet the trajectory of scientific discovery

The Second Challenge on Cross-Domain Few-Shot Object Detection at NTIRE 2026: Methods and Results

arXiv:2604.11998v1 Announce Type: cross Abstract: Cross-domain few-shot object detection (CD-FSOD) remains a challenging problem for existing object detectors and few-shot learning approaches, particu

Think Through Uncertainty: Improving Long-Form Generation Factuality via Reasoning Calibration

arXiv:2604.12046v1 Announce Type: new Abstract: Large language models (LLMs) often hallucinate in long-form generation. Existing approaches mainly improve factuality through post-hoc revision or reinf

TimeMark: A Trustworthy Time Watermarking Framework for Exact Generation-Time Recovery from AIGC

arXiv:2604.12216v1 Announce Type: cross Abstract: The widespread use of Large Language Models (LLMs) in text generation has raised increasing concerns about intellectual property disputes. Watermarkin

To score 100% on a game, you just need to beat the median action efficiency of an unfiltered pool of random people. Easy if you're a bit sma…

researchfrancois-chollet--x

Francois Chollet makes the observation that achieving a perfect score on certain AI benchmark games or tasks only requires surpassing the median performance of an unfiltered random population sample,

Token Encoding for Semantic Recovery

arXiv:2604.12931v1 Announce Type: cross Abstract: Token-based semantic communication is promising for future wireless networks, as it can compact semantic tokens under very limited channel capacity. H

Topology-Aware Reasoning over Incomplete Knowledge Graph with Graph-Based Soft Prompting

arXiv:2604.12503v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown remarkable capabilities across various tasks but remain prone to hallucinations in knowledge-intensive scenari

Towards Realistic and Consistent Orbital Video Generation via 3D Foundation Priors

arXiv:2604.12309v1 Announce Type: new Abstract: We present a novel method for generating geometrically realistic and consistent orbital videos from a single image of an object. Existing video generati

Training single-electron and single-photon stochastic physical neural networks

arXiv:2604.10861v1 Announce Type: cross Abstract: The computational demands of deep learning motivate the investigation of alternative approaches to computation. One alternative is physical neural net

Turbo-DDCM: Fast and Flexible Zero-Shot Diffusion-Based Image Compression

arXiv:2511.06424v2 Announce Type: replace-cross Abstract: While zero-shot diffusion-based compression methods have seen significant progress in recent years, they remain notoriously slow and computati

UCS: Estimating Unseen Coverage for Improved In-Context Learning

arXiv:2604.12015v1 Announce Type: cross Abstract: In-context learning (ICL) performance depends critically on which demonstrations are placed in the prompt, yet most existing selectors prioritize heur

Uncertainty Quantification in CNN Through the Bootstrap of Convex Neural Networks

arXiv:2604.11833v1 Announce Type: new Abstract: Despite the popularity of Convolutional Neural Networks (CNN), the problem of uncertainty quantification (UQ) of CNN has been largely overlooked. Lack o

Unconventional Hexacopters via Evolution and Learning: Performance Gains and New Insights

arXiv:2505.14129v2 Announce Type: replace Abstract: Evolution and learning have historically been interrelated topics, and their interplay is attracting increased interest lately. The emerging new fac

researcharxiv-cs-ro