Search: “research”

PAGaS: Pixel-Aligned 1DoF Gaussian Splatting for Depth Refinement

arXiv:2604.22129v1 Announce Type: new Abstract: Gaussian Splatting (GS) has emerged as an efficient approach for high-quality novel view synthesis. While early GS variants struggled to accurately mode

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Performance Anomaly Detection in Athletics: A Benchmarking System with Visual Analytics

DGX agent

arXiv:2604.21953v1 Announce Type: new Abstract: Anti-doping programs rely on biological testing to detect performance-enhancing drugs, but such testing costs over $800 per sample and is limited by sho

researcharxiv-cs-lg

27 Apr 2026

Point & Grasp: Flexible Selection of Out-of-Reach Objects Through Probabilistic Cue Integration

arXiv:2604.22491v1 Announce Type: cross Abstract: Selecting out-of-reach objects is a fundamental task in mixed reality (MR). Existing methods rely on a single cue or deterministically fuse multiple c

researcharxiv-cs-ro

PoLO: Proof-of-Learning and Proof-of-Ownership at Once with Chained Watermarking

arXiv:2505.12296v2 Announce Type: replace-cross Abstract: Our evaluation shows that PoLO achieves extbf{99%} watermark detection accuracy for ownership verification, while preserving data privacy and

Preference Heads in Large Language Models: A Mechanistic Framework for Interpretable Personalization

arXiv:2604.22345v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit strong implicit personalization ability, yet most existing approaches treat this behavior as a black box, relying o

PreMoE: Proactive Inference for Efficient Mixture-of-Experts

arXiv:2505.17639v3 Announce Type: replace Abstract: Mixture-of-Experts (MoE) models offer dynamic computation, but are typically deployed as static full-capacity models, missing opportunities for depl

Privacy Leakage via Output Label Space and Differentially Private Continual Learning

arXiv:2411.04680v5 Announce Type: replace Abstract: Differential privacy (DP) is a formal privacy framework that enables training machine learning (ML) models while protecting individuals' data. As po

PrivUn: Unveiling Latent Ripple Effects and Shallow Forgetting in Privacy Unlearning

arXiv:2604.22076v1 Announce Type: cross Abstract: Large language models (LLMs) often memorize private information during training, raising serious privacy concerns. While machine unlearning has emerge

Protect the Brain When Treating the Heart: A Convolutional Neural Network for Detecting Emboli

arXiv:2604.22258v1 Announce Type: cross Abstract: Gaseous microemboli (GME) represent a common complication of cardiac structural interventions across both surgical and transcatheter approaches. Trans

Quality-Driven Selective Mutation for Deep Learning

arXiv:2604.22640v1 Announce Type: cross Abstract: Mutants support testing and debugging in two roles: (i) as test goals and (ii) as substitutes for real faults. Hard-to-kill mutants provide better gui

Agents

Read the Paper, Write the Code: Agentic Reproduction of Social-Science Results

arXiv:2604.21965v1 Announce Type: new Abstract: Recent work has used LLM agents to reproduce empirical social science results with access to both the data and code. We broaden this scope by asking: Ca

agentsarxiv-cs-ai

Read the release notes: https://github.com/keras-team/kinetic/releases/tag/0.0.2

researchfrancois-chollet--x

Kinetic version 0.0.2 release notes are available on GitHub, detailing updates and features for this Keras-related project. The announcement was shared by François Chollet, Keras creator, on X (former

ReLIC-SGG: Relation Lattice Completion for Open-Vocabulary Scene Graph Generation

arXiv:2604.22546v1 Announce Type: new Abstract: Open-vocabulary scene graph generation (SGG) aims to describe visual scenes with flexible relation phrases beyond a fixed predicate set. Existing method

Removing Sandbagging in LLMs by Training with Weak Supervision

arXiv:2604.22082v1 Announce Type: cross Abstract: As AI systems begin to automate complex tasks, supervision increasingly relies on weaker models or limited human oversight that cannot fully verify ou

Rethinking Math Reasoning Evaluation: A Robust LLM-as-a-Judge Framework Beyond Symbolic Rigidity

arXiv:2604.22597v1 Announce Type: new Abstract: Recent advancements in large language models have led to significant improvements across various tasks, including mathematical reasoning, which is used

Rethinking Token Pruning for Historical Screenshots in GUI Visual Agents: Semantic, Spatial, and Temporal Perspectives

arXiv:2603.26041v3 Announce Type: replace Abstract: In recent years, GUI visual agents built upon Multimodal Large Language Models (MLLMs) have demonstrated strong potential in navigation tasks. Howev

Revisiting Geometric Obfuscation with Dual Convergent Lines for Privacy-Preserving Image Queries in Visual Localization

arXiv:2604.22310v1 Announce Type: new Abstract: Privacy-Preserving Image Queries (PPIQ) are an emerging mechanism for cloud-based visual localization, enabling pose estimation from obfuscated features

Revisiting Neural Activation Coverage for Uncertainty Estimation

arXiv:2604.22360v1 Announce Type: new Abstract: Neural activation coverage (NAC) is a recently-proposed technique for out-of-distribution detection and generalization. We build upon this promising fou

RouteLMT: Learned Sample Routing for Hybrid LLM Translation Deployment

arXiv:2604.22520v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable performance in Machine Translation (MT), but deploying them at scale remains prohibitively expensi

SAMIDARE: Advanced Tracking-by-Segmentation for Dense Scenarios

arXiv:2604.22162v1 Announce Type: new Abstract: Automated sports analysis demands robust multi-object tracking (MOT), yet segmentation-based methods often struggle with mask errors and ID switches in

Segmentation of Gray Matters and White Matters from Brain MRI data

arXiv:2603.29171v3 Announce Type: replace Abstract: Accurate segmentation of brain tissues such as gray matter and white matter from magnetic resonance imaging is essential for studying brain anatomy,

Selective Rotary Position Embedding

arXiv:2511.17388v2 Announce Type: replace Abstract: Position information is essential for language modeling. In softmax transformers, Rotary Position Embeddings (extit{RoPE}) encode positions through

Semantic Error Correction and Decoding for Short Block Channel Codes

arXiv:2604.22269v1 Announce Type: cross Abstract: This paper presents a semantic-enhanced receiver framework for transmitting natural language sentences over noisy wireless channels using multiple sho

Sensory-Aware Sequential Recommendation via Review-Distilled Representations

arXiv:2603.02709v2 Announce Type: replace-cross Abstract: We propose a novel framework for sensory-aware sequential recommendation that enriches item representations with linguistically extracted sens

Shard the Gradient, Scale the Model: Serverless Federated Aggregation via Gradient Partitioning

arXiv:2604.22072v1 Announce Type: cross Abstract: Federated learning (FL) aggregation on serverless platforms faces a hard scalability ceiling: existing architectures (lambda-FL, LIFL) partition clien

SOC-ICNN: From Polyhedral to Conic Geometry for Learning Convex Surrogate Functions

arXiv:2604.22355v1 Announce Type: new Abstract: Classical ReLU-based Input Convex Neural Networks (ICNNs) are equivalent to the optimal value functions of Linear Programming (LP). This intrinsic struc

Spontaneous Persuasion: An Audit of Model Persuasiveness in Everyday Conversations

arXiv:2604.22109v1 Announce Type: cross Abstract: Large language models (LLMs) possess strong persuasive capabilities that outperform humans in head-to-head comparisons. Users report consulting LLMs t

SS3D: End2End Self-Supervised 3D from Web Videos

arXiv:2604.22686v1 Announce Type: new Abstract: We present SS3D, a web-scale SfM-based self-supervision pretraining pipeline for feed-forward 3D estimation from monocular video. Our model jointly pred

SSG: Logit-Balanced Vocabulary Partitioning for LLM Watermarking

arXiv:2604.22438v1 Announce Type: cross Abstract: Watermarking has emerged as a promising technique for tracing the authorship of content generated by large language models (LLMs). Among existing appr

StateX: Enhancing RNN Recall via Post-training State Expansion

arXiv:2509.22630v3 Announce Type: replace-cross Abstract: Recurrent neural networks (RNNs), such as linear attention and state-space models, have gained popularity due to their constant per-token comp

STEM: Structure-Tracing Evidence Mining for Knowledge Graphs-Driven Retrieval-Augmented Generation

arXiv:2604.22282v1 Announce Type: new Abstract: Knowledge Graph-based Question Answering (KGQA) plays a pivotal role in complex reasoning tasks but remains constrained by two persistent challenges: th

Industry

Study: Infrasound likely a key factor in alleged hauntings

Recent research found that participants exposed to infrasound reported increased irritation, unease, and elevated stress levels regardless of other conditions. While infrasound appears to be one contr

industryars-technica

Tell Me Why: Designing an Explainable LLM-based Dialogue System for Student Problem Behavior Diagnosis

arXiv:2604.22237v1 Announce Type: cross Abstract: Diagnosing student problem behaviors requires teachers to synthesize multifaceted information, identify behavioral categories, and plan intervention s

Tensor Network Estimation of Distribution Algorithms

arXiv:2412.19780v2 Announce Type: replace Abstract: Tensor networks are a tool first employed in the context of many-body quantum physics that now have a wide range of uses across the computational sc

The Exact Replica Threshold for Nonlinear Moments of Quantum States

arXiv:2604.22627v1 Announce Type: cross Abstract: Joint measurements on multiple copies of a quantum state provide access to nonlinear observables such as operatorname{tr}(rho^t), but whether replica

The missing step between hype and profit

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. In February, I picked up a flyer at an anti-AI march in London

researchmit-tech-review

The Shape of Adversarial Influence: Characterizing LLM Latent Spaces with Persistent Homology

arXiv:2505.20435v3 Announce Type: replace-cross Abstract: Existing interpretability methods for Large Language Models (LLMs) predominantly capture linear directions or isolated features. This overlook

Tracing the complexity profiles of different linguistic phenomena through the intrinsic dimension of LLM representations

arXiv:2601.03779v2 Announce Type: replace Abstract: We explore intrinsic dimension (ID) of LLM representations as a marker of linguistic complexity. Specifically, we test whether ID differences across

Uni-Encoder Meets Multi-Encoders: Representation Before Fusion for Brain Tumor Segmentation with Missing Modalities

arXiv:2604.22177v1 Announce Type: new Abstract: Multimodal MRI offers complementary information for brain tumor segmentation, but clinical scans often lack one or more modalities, which degrades segme

UniSonate: A Unified Model for Speech, Music, and Sound Effect Generation with Text Instructions

arXiv:2604.22209v1 Announce Type: cross Abstract: Generative audio modeling has largely been fragmented into specialized tasks, text-to-speech (TTS), text-to-music (TTM), and text-to-audio (TTA), each

V-MAGE: A Game Evaluation Framework for Assessing Vision-Centric Capabilities in Multimodal Large Language Models

arXiv:2504.06148v3 Announce Type: replace Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in visual-text processing. However, existi

Verbal Confidence Saturation in 3-9B Open-Weight Instruction-Tuned LLMs: A Pre-Registered Psychometric Validity Screen

arXiv:2604.22215v1 Announce Type: cross Abstract: Verbal confidence elicitation is widely used to extract uncertainty estimates from LLMs. We tested whether seven instruction-tuned open-weight models

Voice Under Revision: Large Language Models and the Normalization of Personal Narrative

arXiv:2604.22142v1 Announce Type: new Abstract: This study examines how large language model rewriting alters the style and narrative texture of personal narratives. It analyzes 300 personal narrative

When LoRA Betrays: Backdooring Text-to-Image Models by Masquerading as Benign Adapters

arXiv:2602.21977v4 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has emerged as a leading technique for efficiently fine-tuning text-to-image diffusion models, and its widespread adoptio

Where Should LoRA Go? Component-Type Placement in Hybrid Language Models

arXiv:2604.22127v1 Announce Type: new Abstract: Hybrid language models that interleave attention with recurrent components are increasingly competitive with pure Transformers, yet standard LoRA practi

Zero-Shot Morphological Discovery in Low-Resource Bantu Languages via Cross-Lingual Transfer and Unsupervised Clustering

arXiv:2604.22723v1 Announce Type: cross Abstract: We present a method for discovering morphological features in low-resource Bantu languages by combining cross-lingual transfer learning with unsupervi

Describe Seattle:

researchfrancois-chollet--x

Describe Seattle: I want to live near the sea and I want to live near the forest and I want to live near the mountains and I want to live near a café and I want to live near a library and I want to li

26 Apr 2026

If you want to get dumber, confused, and lacking any situational awareness, listen to anonymous 'AI influencer' drivel accounts...