All entries

Evaluating the Interpretability of Sparse Autoencoders with Concept Annotations

arXiv:2606.24716v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) are increasingly used to extract interpretable concepts from vision and vision language models, yet existing evaluation met

Evaluation Metrics as Averaged Outcomes of Fair Gambles

DGX agent

arXiv:2401.14483v4 Announce Type: replace Abstract: In the current practices of machine learning, the evaluation of forecasts has become a cornerstone of scientific progress. A multitude of evaluation

researcharxiv-cs-lg

24 Jun 2026

Applications

Event-Aligned Analysis of Multi-Rater Pain Assessments Using Continuous Wearable Physiology

arXiv:2606.23705v1 Announce Type: cross Abstract: Pain is assessed differently by patients, nurses, and clinicians, yet most computational approaches assume a single ground-truth label - effectively i

applicationsarxiv-cs-ai

Event-Grounded Question Answering over Long Audio via Structured Retrieval

arXiv:2602.14612v4 Announce Type: replace-cross Abstract: Answering natural-language questions over multi-hour audio requires both event recognition and temporal grounding. Current large audio-languag

local-aiarxiv-cs-ai

EvidenceLens: A Claim-Evidence Matrix for Auditing Financial Question Answering

arXiv:2606.23724v1 Announce Type: cross Abstract: Large language models are increasingly used to answer questions over annual reports, earnings decks, and analyst notes, yet their outputs remain diffi

safetyarxiv-cs-cl

Evolving Programmatic Skill Networks

arXiv:2601.03509v2 Announce Type: replace Abstract: We study continual skill acquisition in open-ended embodied environments where an agent must construct, refine, and reuse an expanding library of ex

agentsarxiv-cs-ai

Exact Schur-Sylvester Dimensionality Reductions for Non-Smooth Stochastic Complexity and Manifold Sampling

arXiv:2606.23867v1 Announce Type: new Abstract: The exact computation of the Normalized Maximum Likelihood (NML) codelength for regular non-smooth estimators (e.g., Lasso) has been historically limite

researcharxiv-cs-lg

Excited to partner with @OpenRouter ⚡ Products like OpenRouter Fusion and Sakana Fugu have sparked a serious conversation about dependency a…

Excited to partner with @OpenRouter ⚡ Products like OpenRouter Fusion and Sakana Fugu have sparked a serious conversation about dependency and resilience in AI. I believe this is just the start of a g

researchdavid-ha--x

Experimental wine bottle tracks oxygen moving through the cork

French researchers designed experimental glass tubes mimicking wine bottle necks and used fluorescent sensors to track oxygen movement through corks over 18 months without opening them. By varying cor

industryars-technica

Experiments with Optimal Model Trees

model-releasesarxiv-cs-lg

arXiv:2503.12902v4 Announce Type: replace Abstract: Model trees provide an appealing way to perform interpretable machine learning for both classification and regression problems. In contrast to ``cla

Explaining Failures of Cyber-Physical Systems with Actual Causality

arXiv:2606.24546v1 Announce Type: new Abstract: Modern autonomous Cyber-Physical Systems (CPSs), such as self-driving cars, face increasingly complex demands, and yet are expected to act reliably. The

agentsarxiv-cs-ro

Exploring Academic Influence of Algorithms by Co-occurrence Network Based on Full-text of Academic Papers

arXiv:2606.24099v1 Announce Type: new Abstract: Algorithms have become central to scientific research in the era of artificial intelligence (AI). Although algorithm mentions in papers are often used t

Exploring Dualistic Meta-Learning to Enhance Domain Generalization in Open Set Scenarios

arXiv:2606.23758v1 Announce Type: cross Abstract: Domain generalization learns from multiple source domains to generalize to unseen target domains. However, it often neglects the realistic case of lab

Exploring the relationship between human-centric AI and firm idiosyncratic risks

arXiv:2606.24224v1 Announce Type: new Abstract: Despite the extensive discussions of human-centric AI (HCAI) in Industry 5.0, its effects on firms' idiosyncratic risks (IR) remains underexplored. This

EXPO-SQL: Execution-based Clause-level Policy Optimization for Text-to-SQL

arXiv:2606.23693v1 Announce Type: new Abstract: Text-to-SQL enables users to query databases using natural language by generating executable SQL queries. Recent methods have increasingly adopted Large

safetyarxiv-cs-cl

Extended pseudo-spectral physics-informed neural networks for phase-field models

model-releasesarxiv-cs-lg

arXiv:2606.24660v1 Announce Type: cross Abstract: Phase-field models play a central role in the continuum description of phase separation, in which the bulk free-energy density and the interfacial thi

Fabric Image Demoireing Benchmark from Synthesis to Restoration

model-releasesarxiv-cs-cv

arXiv:2606.24072v1 Announce Type: new Abstract: Fabric moire is a sampling-induced aliasing artifact caused by the interaction between fine textile patterns and camera sensor grids, producing structur

Faithful by Construction: Claim-Anchored Attribution for Multi-Document Summarization

arXiv:2606.23989v1 Announce Type: cross Abstract: End-to-end large language models (LLMs) produce fluent multi-document summaries but remain prone to hallucination, and the attributions they offer are

local-aiarxiv-cs-ai

FALCON: Transforming Cyber Threat Intelligence into Deployable IDS Rules with Self-Reflection

arXiv:2508.18684v2 Announce Type: replace-cross Abstract: Signature-based Intrusion Detection Systems (IDS) detect malicious activity by matching network or host events against predefined rules. Secur

Tutorials

Fast and Slow Variational Continual Learning

arXiv:2606.24007v1 Announce Type: cross Abstract: Continual learning remains a major challenge for modern deep networks, partly because commonly used optimizers lack inherent mechanisms for continual

tutorialsarxiv-cs-ai

FCC plans ID mandate that could block anonymous use of prepaid burner phones

The FCC is considering new rules that would require phone companies to collect government IDs and physical addresses from customers to combat scam calls and robocalls. Privacy advocates warn the propo

industryars-technica

Federated Survival Analysis in Healthcare: A Multi-Model Evaluation on Cross-Institutional Heterogeneous Breast Cancer Data

arXiv:2606.23871v1 Announce Type: new Abstract: Survival analysis is central to clinical decision-making, yet reliable time-to-event models require large, diverse cohorts that are rarely available at

local-aiarxiv-cs-lg

Applications

FedUP: One-Shot Federated Unlearning via Centroid-Guided Plug-in Filters

arXiv:2606.24113v1 Announce Type: new Abstract: Federated unlearning (FU) is critical for complying with legal mandates like the right to be forgotten in decentralized systems, yet current methods fac

applicationsarxiv-cs-lg

Female-RHINO: A Real-Time Scanner-Integrated Framework for Automated Quantitative Uterine MRI Analysis and Structured Reporting

arXiv:2606.24390v1 Announce Type: cross Abstract: Standardized assessment of uterine MRI remains challenging due to anatomical variability, observer dependence, and the lack of workflow-integrated aut

Few shot chain-of-thought driven reasoning to prompt LLMs for open ended medical question answering

arXiv:2403.04890v4 Announce Type: replace Abstract: In this paper, we propose a modified version of the MedQA-USMLE dataset, named MEDQA-OPEN, which contains open-ended medical questions without optio

researcharxiv-cs-cl

FiCA: Feed-forward instant Gaussian Codec Avatars from a Single Portrait Image

arXiv:2606.24232v1 Announce Type: new Abstract: We introduce FiCA, a Feed-forward, instant Gaussian Codec Avatar generation pipeline that creates lifelike avatars from a single portrait image. Generat

researcharxiv-cs-cv

Figma now has AI motion graphics and shader tools

Figma has revealed some new design and coding product updates at its annual Config conference that aim to help creatives 'push their ideas further' and automate tedious tasks with AI. Part of this is

industrythe-verge-ai

Finally caved in, and I now fully speak to agents as opposed to typing prompts. My first realization is that you can just blabber on and tel…

Finally caved in, and I now fully speak to agents as opposed to typing prompts. My first realization is that you can just blabber on and tell the agent so many rich details via audio. The longer and t

agentsdair-ai--x

Fine-Grained Open-Vocabulary Object Detection with Fined-Grained Prompts: Task, Dataset and Benchmark

model-releasesarxiv-cs-cv

arXiv:2503.14862v3 Announce Type: replace Abstract: Open-vocabulary detectors are proposed to locate and recognize objects in novel classes. However, variations in vision-aware language vocabulary dat

FISHER: A Foundation Model for Multi-Modal Industrial Signal Comprehensive Representation

arXiv:2507.16696v3 Announce Type: replace-cross Abstract: Industrial signal analysis is hindered by severe data heterogeneity, which we characterize as the M5 problem. Existing solutions rely on speci

FLAT: Feedforward Latent Triangle Splatting for Geometrically Accurate Scene Generation

arXiv:2606.24876v1 Announce Type: new Abstract: Generating explorable 3D scenes from a single image requires strong generative priors and accurate geometric representations suitable for downstream use

researcharxiv-cs-cv

Flood Mapping from RGB imagery using a Vision Foundation Model

arXiv:2606.24120v1 Announce Type: new Abstract: Timely, high-resolution maps of flood extent around settlements are essential for emergency response and damage assessment. We consider airborne RGB ima

researcharxiv-cs-cv

Flow-Corrected Thompson Sampling for Non-Stationary Contextual Bandits

model-releasesarxiv-cs-lg

arXiv:2606.23933v1 Announce Type: cross Abstract: We study non-stationary linear contextual bandits where the reward model drifts over time, rendering classical contextual bandit algorithms brittle be

FlowerDance: MeanFlow for Efficient and Refined 3D Dance Generation

model-releasesarxiv-cs-cv

arXiv:2511.21029v3 Announce Type: replace Abstract: Music-to-dance generation aims to translate auditory signals into expressive human motion, with broad applications in virtual reality, choreography,

FlowPipe: LLM-Enhanced Conditional Generative Flow Networks for Data Preparation Pipeline Construction

arXiv:2606.24679v1 Announce Type: cross Abstract: Data preparation pipelines improve data quality in machine learning by transforming raw tables into learning-ready data through sequential cleaning an

FlowR2A: Learning Reward-to-Action Distribution for Multimodal Driving Planning

arXiv:2606.24231v1 Announce Type: new Abstract: Multimodal driving planning faces a long-standing tension between two paradigms: scoring-based methods benefit from dense reward supervision but are con

FLUX3D: High-Fidelity 3D Gaussian Generation with Diffusion-Aligned Sparse Representation

arXiv:2606.24874v1 Announce Type: cross Abstract: Sparse voxel representation has emerged as a scalable foundation for image-to-3D Gaussian Splatting (3DGS) generation, yet current methods struggle to

ForensicsTok: Forensics-Guided Tokenized Modeling for Image Tampering Localization

arXiv:2606.24538v1 Announce Type: new Abstract: Multi-modal Large Language Models (MLLMs) offer powerful reasoning for forensic tasks, yet existing approaches utilizing exogenous segmentation decoders

local-aiarxiv-cs-cv

Forget Without Compromise: Nexus Sampling for Streaming KV-Cache Eviction Under Fixed Budgets

arXiv:2606.23961v1 Announce Type: new Abstract: Long-context and agentic LLM workloads push the KV cache past any fixed memory budget, forcing the inference stack to permanently evict tokens at every

agentsarxiv-cs-lg

Formula E reveals first calendar for GEN4 with lots of real race tracks

Formula E announced its first calendar for the 2026-27 GEN4 era featuring a record 21 races across 13 cities, with three new permanent circuit venues including COTA in Austin, Brands Hatch in London,

industryars-technica

Foundations of Practical Quantum Advantage in Quantum-Informed Machine Learning for Predicting Chaos

arXiv:2606.13422v2 Announce Type: replace-cross Abstract: We develop theoretical foundations for a practical quantum-advantage mechanism in quantum-informed machine learning for chaotic dynamical syst

researcharxiv-cs-lg

FP8 is All You Need (Part 2): Efficient Ozaki-Bailey Style FFT Through Tensor-core Garner Reformulation and Kulisch Escape Route

arXiv:2606.23698v1 Announce Type: cross Abstract: NVIDIA's Blackwell Ultra (B300) cuts FP64 vector throughput to ~1.3 TFLOPS per GPU, roughly 30x below B200 and well below the level at which bandwidth

From 'Aha Moments' to Controllable Thinking: Toward Meta-Cognitive Reasoning in Large Reasoning Models via Decoupled Reasoning and Control

arXiv:2508.04460v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) can exhibit step-by-step reasoning, reflection, and backtracking, but these behaviors are often unregulated, leading t

From Local Corrections to Generalized Skills: Improving Neuro-Symbolic Policies with MEMO

arXiv:2603.04560v2 Announce Type: replace Abstract: Recent works use a neuro-symbolic framework for general manipulation policies. The advantage of this framework is that -- by applying off-the-shelf

safetyarxiv-cs-ro

From Open Waters to Enclosed Cabins: ProteusVPR for Cross-Scene Visual Place Recognition in Maritime Perception and Cabin Inspection

arXiv:2606.24234v1 Announce Type: new Abstract: Autonomous robotic inspection in maritime environments presents unique challenges for Visual Place Recognition (VPR) due to cross-scene perceptual shift

agentsarxiv-cs-cv

From Singleton Obstacles to Clutter: Translation Invariant Compositional Avoid Sets

arXiv:2603.22146v2 Announce Type: replace-cross Abstract: This paper studies obstacle avoidance under translation invariant dynamics using an avoid-side travel cost Hamilton Jacobi formulation. For ru

researcharxiv-cs-ro

From Spatial to Spectral: An Efficient, Frequency-Guided Feature Representation Learner for Small Object Detection

arXiv:2606.23825v1 Announce Type: cross Abstract: Efficient small object detection is bottlenecked by the inherent feature scarcity of tiny targets, which is further aggravated by operations of spatia

From Task-Guided Conversational Graphs to Goal-Oriented Dialogue Runtimes

arXiv:2606.23797v1 Announce Type: cross Abstract: Graph and multi-agent orchestration frameworks make production large language model (LLM) workflows practical, but they do not by themselves solve con

agentsarxiv-cs-ai