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Product Quantization for Surface Soil Similarity

arXiv:2506.03374v2 Announce Type: replace Abstract: The use of machine learning (ML) techniques has allowed rapid advancements in many scientific and engineering fields. One of these problems is that

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Projected Gradient Unlearning for Text-to-Image Diffusion Models: Defending Against Concept Revival Attacks

DGX agent

arXiv:2604.21041v1 Announce Type: new Abstract: Machine unlearning for text-to-image diffusion models aims to selectively remove undesirable concepts from pre-trained models without costly retraining.

researcharxiv-cs-cv

24 Apr 2026

Propensity Inference: Environmental Contributors to LLM Behaviour

arXiv:2604.21098v1 Announce Type: new Abstract: Motivated by loss of control risks from misaligned AI systems, we develop and apply methods for measuring language models' propensity for unsanctioned b

Prototype-Based Test-Time Adaptation of Vision-Language Models

arXiv:2604.21360v1 Announce Type: new Abstract: Test-time adaptation (TTA) has emerged as a promising paradigm for vision-language models (VLMs) to bridge the distribution gap between pre-training and

ReaGeo: Reasoning-Enhanced End-to-End Geocoding with LLMs

arXiv:2604.21357v1 Announce Type: new Abstract: This paper proposes ReaGeo, an end-to-end geocoding framework based on large language models, designed to overcome the limitations of traditional multi-

🎓 Register now for ML & Advanced Stats Summer School, an intensive set of courses on theoretical foundations & applications of ML methods &…

🎓 Register now for ML & Advanced Stats Summer School, an intensive set of courses on theoretical foundations & applications of ML methods & modern stats analysis techniques. With @ELLISUnitMadrid. 📍 M

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Relocation of compact sets in R^n by diffeomorphisms and linear separability of datasets in R^n

arXiv:2604.21393v1 Announce Type: new Abstract: Relocation of compact sets in an n-dimensional manifold by self-diffeomorphism is of its own interest as well as significant potential applications to d

Replay-buffer engineering for noise-robust quantum circuit optimization

arXiv:2604.21863v1 Announce Type: cross Abstract: Deep reinforcement learning (RL) for quantum circuit optimization faces three fundamental bottlenecks: replay buffers that ignore the reliability of t

Reversible Deep Learning for 13C NMR in Chemoinformatics: On Structures and Spectra

arXiv:2602.03875v4 Announce Type: replace-cross Abstract: We introduce a reversible deep learning model for 13C NMR that uses a single conditional invertible neural network for both directions between

Revisiting Content-Based Music Recommendation: Efficient Feature Aggregation from Large-Scale Music Models

arXiv:2604.20847v1 Announce Type: cross Abstract: Music Recommendation Systems (MRSs) are a cornerstone of modern streaming platforms. Existing recommendation models, spanning both recall and ranking

Revisiting Non-Verbatim Memorization in Large Language Models: The Role of Entity Surface Forms

arXiv:2604.21882v1 Announce Type: new Abstract: Understanding what kinds of factual knowledge large language models (LLMs) memorize is essential for evaluating their reliability and limitations. Entit

RV-HATE: Reinforced Multi-Module Voting for Implicit Hate Speech Detection

arXiv:2510.10971v2 Announce Type: replace-cross Abstract: Hate speech remains prevalent in human society and continues to evolve in its forms and expressions. Modern advancements in internet and onlin

@SakanaAILabs Sign up below to get a bunch of free API credits and test our Fugu orchestration models on your workflows. 🐡 Blog: https://sa…

Sakana AI Labs is offering free API credits for developers to test their Fugu orchestration models in real workflows. The offer was announced by David Ha on X, with additional details available on the

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Satisfying Rationality Postulates of Structured Argumentation Through Deductive Support -- Technical Report

arXiv:2604.21515v1 Announce Type: new Abstract: ASPIC-style structured argumentation frameworks provide a formal basis for reasoning in artificial intelligence by combining internal argument structure

Scensory: Real-Time Robotic Olfactory Perception for Joint Identification and Source Localization

arXiv:2509.19318v2 Announce Type: replace-cross Abstract: While robotic perception has advanced rapidly in vision and touch, enabling robots to reason about indoor fungal contamination from weak, diff

researcharxiv-cs-ro

Schoenfeld's Anatomy of Mathematical Reasoning by Language Models

arXiv:2512.19995v2 Announce Type: replace-cross Abstract: Large language models increasingly expose reasoning traces, yet their underlying cognitive structure and steps remain difficult to identify an

Sculpt4D: Generating 4D Shapes via Sparse-Attention Diffusion Transformers

arXiv:2604.21592v1 Announce Type: new Abstract: Recent breakthroughs in 3D generative modeling have yielded remarkable progress in static shape synthesis, yet high-fidelity dynamic 4D generation remai

SDNGuardStack: An Explainable Ensemble Learning Framework for High-Accuracy Intrusion Detection in Software-Defined Networks

arXiv:2604.20934v1 Announce Type: cross Abstract: Software-Defined Networking (SDN) is another technology that has been developing in the last few years as a relevant technique to improve network prog

SemanticAgent: A Semantics-Aware Framework for Text-to-SQL Data Synthesis

arXiv:2604.21414v1 Announce Type: new Abstract: Existing text-to-SQL synthesis pipelines still conflate executability with semantic validity: syntactic checks and execution-based validation can retain

SemEval-2026 Task 4: Narrative Story Similarity and Narrative Representation Learning

arXiv:2604.21782v1 Announce Type: new Abstract: We present the shared task on narrative similarity and narrative representation learning - NSNRL (pronounced 'nass-na-rel'). The task operationalizes na

SGD at the Edge of Stability: The Stochastic Sharpness Gap

arXiv:2604.21016v1 Announce Type: cross Abstract: When training neural networks with full-batch gradient descent (GD) and step size eta, the largest eigenvalue of the Hessian -- the sharpness S(oldsym

Sink-Token-Aware Pruning for Fine-Grained Video Understanding in Efficient Video LLMs

arXiv:2604.20937v1 Announce Type: new Abstract: Video Large Language Models (Video LLMs) incur high inference latency due to a large number of visual tokens provided to LLMs. To address this, training

Slot Machines: How LLMs Keep Track of Multiple Entities

arXiv:2604.21139v1 Announce Type: new Abstract: Language models must bind entities to the attributes they possess and maintain several such binding relationships within a context. We study how multipl

Spatio-temporal probabilistic forecast using MMAF-guided learning

arXiv:2603.15055v2 Announce Type: replace-cross Abstract: We present a theory-guided generalized Bayesian methodology for spatio-temporal raster data, which we use to train an ensemble of stochastic f

Spectral Kernel Dynamics for Planetary Surface Graphs: Distinction Dynamics and Topological Conservation

arXiv:2604.20887v1 Announce Type: cross Abstract: The spectral kernel field equation R[k] = T[k] lacks a conservation-law analog. We prove (i) the fixed-point flow is strictly volume-expanding (tr DF

SPIRE: Structure-Preserving Interpretable Retrieval of Evidence

arXiv:2604.20849v1 Announce Type: cross Abstract: Retrieval-augmented generation over semi-structured sources such as HTML is constrained by a mismatch between document structure and the flat, sequenc

StegoStylo: Squelching Stylometric Scrutiny through Steganographic Stitching

arXiv:2601.09056v3 Announce Type: replace-cross Abstract: Stylometry--the identification of an author through analysis of a text's style (i.e., authorship attribution)--serves many constructive purpos

StructMem: Structured Memory for Long-Horizon Behavior in LLMs

arXiv:2604.21748v1 Announce Type: cross Abstract: Long-term conversational agents need memory systems that capture relationships between events, not merely isolated facts, to support temporal reasonin

Sub-Token Routing in LoRA for Adaptation and Query-Aware KV Compression

arXiv:2604.21335v1 Announce Type: cross Abstract: Sub-token routing offers a finer control axis for transformer efficiency than the coarse units used in most prior work, such as tokens, pages, heads,

TAPO-Description Logic for Information Behavior: Refined OBoxes, Inference, and Categorical Semantics

arXiv:2604.21172v1 Announce Type: cross Abstract: This paper develops a refined version of TAPO-description logic for the analysis of information behavior. The framework is treated not as a single hom

Ternary Memristive Logic: Hardware for Reasoning Realized via Domain Algebra

arXiv:2604.20891v1 Announce Type: cross Abstract: Memristive crossbars store numerical weights needing aggregation and decoding; a single junction means nothing alone. This paper presents a fundamenta

Thank you to @Kimi_Moonshot for adding an additional $1000 to the prize pool in honor of the Kimi 2.6 release

Nous Research announced that Kimi_Moonshot contributed an additional $1000 to a prize pool in celebration of the Kimi 2.6 release. This sponsorship gesture increased the total available prizes for wha

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The CriticalSet problem: Identifying Critical Contributors in Bipartite Dependency Networks

arXiv:2604.21537v1 Announce Type: new Abstract: Identifying critical nodes in complex networks is a fundamental task in graph mining. Yet, methods addressing an all-or-nothing coverage mechanics in a

The Sample Complexity of Multicalibration

arXiv:2604.21923v1 Announce Type: new Abstract: We study the minimax sample complexity of multicalibration in the batch setting. A learner observes n i.i.d. samples from an unknown distribution and mu

The web is disappearing 🕳️ According to a Pew Research Center report, 26% of pages from 2013-2023 are no longer accessible. But that’s not …

The web is disappearing 🕳️ According to a Pew Research Center report, 26% of pages from 2013-2023 are no longer accessible. But that’s not the whole story. In a new study published in Internet Archive

researchyann-lecun--x

There Will Be a Scientific Theory of Deep Learning

arXiv:2604.21691v1 Announce Type: cross Abstract: In this paper, we make the case that a scientific theory of deep learning is emerging. By this we mean a theory which characterizes important properti

TRACES: Tagging Reasoning Steps for Adaptive Cost-Efficient Early-Stopping

arXiv:2604.21057v1 Announce Type: new Abstract: The field of Language Reasoning Models (LRMs) has been very active over the past few years with advances in training and inference techniques enabling L

Transferable SCF-Acceleration through Solver-Aligned Initialization Learning

arXiv:2604.21657v1 Announce Type: new Abstract: Machine learning methods that predict initial guesses from molecular geometry can reduce this cost, but matrix-prediction models fail when extrapolating

Transformer-Progressive Mamba Network for Lightweight Image Super-Resolution

arXiv:2511.03232v2 Announce Type: replace Abstract: Recently, Mamba-based super-resolution (SR) methods have demonstrated the ability to capture global receptive fields with linear complexity, address

Tuning for TraceTarnish: Techniques, Trends, and Testing Tangible Traits

arXiv:2512.03465v3 Announce Type: replace-cross Abstract: In this study, we more rigorously evaluated our attack script extit{TraceTarnish}, which leverages adversarial stylometry principles to anonym

UAU-Net: Uncertainty-aware Representation Learning and Evidential Classification for Facial Action Unit Detection

arXiv:2604.21227v1 Announce Type: new Abstract: Facial action unit (AU) detection remains challenging because it involves heterogeneous, AU-specific uncertainties arising at both the representation an

UbiQVision: Quantifying Uncertainty in XAI for Image Recognition

arXiv:2512.20288v2 Announce Type: replace-cross Abstract: Recent advances in deep learning have led to its widespread adoption across diverse domains, including medical imaging. This progress is drive

UKP_Psycontrol at SemEval-2026 Task 2: Modeling Valence and Arousal Dynamics from Text

arXiv:2604.21534v1 Announce Type: new Abstract: This paper presents our system developed for SemEval-2026 Task 2. The task requires modeling both current affect and short-term affective change in chro

Unlocking the Power of Large Language Models for Multi-table Entity Matching

arXiv:2604.21238v1 Announce Type: new Abstract: Multi-table entity matching (MEM) addresses the limitations of dual-table approaches by enabling simultaneous identification of equivalent entities acro

Unsupervised Learning of Inter-Object Relationships via Group Homomorphism

arXiv:2604.20925v1 Announce Type: new Abstract: While current deep learning models achieve high performance by learning statistical correlations from vast datasets,which stands in stark contrast to hu

Using ASP(Q) to Handle Inconsistent Prioritized Data

arXiv:2604.21603v1 Announce Type: cross Abstract: We explore the use of answer set programming (ASP) and its extension with quantifiers, ASP(Q), for inconsistency-tolerant querying of prioritized data

Validating a Deep Learning Algorithm to Identify Patients with Glaucoma using Systemic Electronic Health Records

arXiv:2604.20921v1 Announce Type: new Abstract: We evaluated whether a glaucoma risk assessment (GRA) model trained on All of Us national data can identify patients at high probability of glaucoma usi

Verifying Machine Learning Interpretability Requirements through Provenance

arXiv:2604.21599v1 Announce Type: cross Abstract: Machine Learning (ML) Engineering is a growing field that necessitates an increase in the rigor of ML development. It draws many ideas from software e