All entries

Flow Matching with Optimized Subclass Priors for Medical Image Augmentation

arXiv:2605.16469v1 Announce Type: cross Abstract: Rare diseases dominate the diagnostic challenge in medical imaging yet are severely underrepresented in clinical datasets, causing classifiers to fail

safetyarxiv-cs-cv

Flowing with Confidence

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

arXiv:2605.18472v1 Announce Type: cross Abstract: Generative models can produce nonsensical text, unrealistic images, and unstable materials faster than simulation or human review can absorb; without

researcharxiv-cs-ai

19 May 2026

FlowMixer: A Depth-Agnostic Neural Architecture for Interpretable Spatiotemporal Forecasting

arXiv:2505.16786v2 Announce Type: replace Abstract: We introduce FlowMixer, a single-layer neural architecture that leverages constrained matrix operations to model structured spatiotemporal patterns

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics

arXiv:2605.17373v1 Announce Type: cross Abstract: AI research agents accelerate ML research by automating hypothesis generation, experimentation, and empirical refinement. Existing agent strategies ra

Focused Forcing: Content-Aware Per-Frame KV Selection for Efficient Autoregressive Video Diffusion

arXiv:2605.18346v1 Announce Type: cross Abstract: Recent advances in autoregressive video diffusion have enabled sequential and streaming video generation. However, long-horizon generation requires in

FOL2NS: Generating Natural Sentences from First-Order Logic

arXiv:2605.18155v1 Announce Type: new Abstract: Translating formal language into natural language is a foundational challenge in NLP, driving various downstream applications in semantic parsing, theor

Forecasting Downstream Performance of LLMs With Proxy Metrics

arXiv:2605.18607v1 Announce Type: new Abstract: Progress in language model development is often driven by comparative decisions: which architecture to adopt, which pretraining corpus to use, or which

Forecasting Medium-Horizon Alzheimer's Disease Progression: Residual Gap-Aware Transformers for 24-Month CDR-SB Change from ADNI Clinical and Biomarker Histories

arXiv:2605.16319v1 Announce Type: new Abstract: Medium-horizon Alzheimer's disease progression prediction is difficult because future clinical scores can remain tied to baseline severity, while biomar

Forget-It-All: Multi-Concept Machine Unlearning via Concept-Aware Neuron Masking

arXiv:2601.06163v2 Announce Type: replace Abstract: The widespread adoption of text-to-image (T2I) diffusion models has raised concerns about their potential to generate copyrighted, inappropriate, or

Forget Many, Forget Right: Scalable and Precise Concept Unlearning in Diffusion Models

arXiv:2601.06162v4 Announce Type: replace-cross Abstract: Text-to-image diffusion models have achieved remarkable progress, yet their use raises copyright and misuse concerns, prompting research into

safetyarxiv-cs-cv

Forgetting is Competition: Rethinking Unlearning as Representation Interference in Diffusion Models

arXiv:2603.00975v2 Announce Type: replace-cross Abstract: Deployed text-to-image diffusion models increasingly require post-hoc concept unlearning for copyright claims, artist opt-outs, safety updates

Form and Function: Machine Unlearning as a Problem of Misaligned States

model-releasesarxiv-cs-lg

arXiv:2605.17590v1 Announce Type: new Abstract: We formulate machine unlearning for online L-BFGS as a counterfactual state-alignment problem. Given an actual event stream and a deletion-edited counte

FormuLLA: A Large Language Model Approach to Generating Novel 3D Printable Formulations

arXiv:2601.02071v3 Announce Type: replace Abstract: Pharmaceutical three-dimensional (3D) printing is an advanced fabrication technology with the potential to enable truly personalised dosage forms. R

Tutorials

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster

arXiv:2605.18204v1 Announce Type: cross Abstract: Discrete diffusion models are a powerful class of generative models with strong performance across many domains. For efficiency, however, discrete dif

tutorialsarxiv-cs-lg

Foundation Models for Credit Risk Prediction: A Game Changer?

arXiv:2605.18147v1 Announce Type: new Abstract: Predictive models play a pivotal role in credit risk management, guiding critical decisions through accurate estimation of default probabilities and los

Fourier Compressor: Frequency-Domain Visual Token Compression for Vision-Language Models

arXiv:2508.06038v3 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) incur substantial computational overhead and inference latency due to the large number of vision tokens introduc

fPINN-DeepONet: A Physics-Informed Operator Learning Framework for Multi-term Time-fractional Mixed Diffusion-wave Equations

arXiv:2605.16594v1 Announce Type: cross Abstract: In this paper, we develop a physics-informed deep operator learning framework for solving multi-term time-fractional mixed diffusion-wave equations (T

Fre-Res: Frequency-Residual Video Token Compression for Efficient Video MLLMs

arXiv:2605.16366v1 Announce Type: cross Abstract: Video MLLMs face a persistent tension between spatial fidelity and temporal coverage: preserving fine-grained visual details requires many spatial tok

researcharxiv-cs-ai

Local Ai

FrequencyBooster: Full-Frequency Modeling for High-Fidelity Pixel Diffusion

arXiv:2605.17759v1 Announce Type: new Abstract: To circumvent the inherent fidelity bottlenecks and optimization misalignment of VAE-based latent diffusion, pixel-space diffusion models have emerged a

local-aiarxiv-cs-cv

Local Ai

Friends and Grandmothers in Silico: Localizing Entity Cells in Language Models

arXiv:2604.01404v2 Announce Type: replace-cross Abstract: How do language models retrieve entity-specific facts from their parameters? We investigate this question by searching for sparse, entity-sele

local-aiarxiv-cs-ai

From a Single Demonstration to a General Policy for Contact-Rich Manipulation

arXiv:2605.17601v1 Announce Type: new Abstract: We present a Learning from Demonstration (LfD) framework that achieves one-shot generalization in multi-stage, contact-rich manipulation tasks. Central

safetyarxiv-cs-ro

From BERT to T5: A Study of Named Entity Recognition

arXiv:2605.18462v1 Announce Type: new Abstract: Named entity recognition (NER) has been one of the essential preliminary steps in modern NLP applications. This report focuses on implementing the NER t

From Demographics to Survey Anchors: Evaluating LLM Agents for Modeling Retirement Attitudes

arXiv:2605.16303v1 Announce Type: cross Abstract: Large language models (LLM) agents may offer tools to predict human responses to surveys. A common technique for defining these agents uses only demog

Applications

From Documents to Segments: A Contextual Reformulation for Topic Assignment

arXiv:2605.17714v1 Announce Type: new Abstract: Traditional topic modeling assigns a single topic to each document. In practice, however, many real-world documents, such as product reviews or open-end

applicationsarxiv-cs-cl

From Imitation to Interaction: Mastering Game of Schnapsen with Shallow Reinforcement Learning

arXiv:2605.17162v1 Announce Type: new Abstract: This paper investigates whether shallow neural network agents can master the card game Schnapsen and challenge a strong search-based baseline, RdeepBot,

From Isolated Scoring to Collaborative Ranking: A Comparison-Native Framework for LLM-Based Paper Evaluation

arXiv:2603.17588v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are currently applied to scientific paper evaluation by assigning an absolute score to each paper independently.

From Pixels to Places: A Systematic Benchmark for Evaluating Image Geolocalization Ability in Large Language Models

model-releasesarxiv-cs-cv

arXiv:2508.01608v2 Announce Type: replace Abstract: Image geolocalization, the task of identifying the geographic location depicted in an image, is important for applications in crisis response, digit

Tutorials

From Prediction to Intervention: The Evolution of AI in Biomedicine

arXiv:2605.16293v1 Announce Type: cross Abstract: Artificial intelligence has advanced rapidly in biomedicine through large-scale multimodal data integration, enabling increasingly accurate prediction

tutorialsarxiv-cs-ai

Agents

From Prompts to Protocols: An AI Agent for Laboratory Automation

arXiv:2605.16552v1 Announce Type: new Abstract: Automating science laboratories enables faster, safer, more accurate, and more reproducible execution of protocols, accelerating the discovery and testi

agentsarxiv-cs-ai

From Reactive to Proactive: A Multi-Regulatory Empirical Analysis of 480 AI Incidents and a Data-Driven Governance Compliance Framework

arXiv:2605.16281v1 Announce Type: cross Abstract: Artificial intelligence systems are increasingly deployed in high-stakes domains, yet it remains unclear whether existing governance frameworks ensure

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction

arXiv:2605.16927v1 Announce Type: new Abstract: Clinical decision-making is a feedback system where risk estimates influence treatment, which in turn changes disease trajectories, and both shape clini

Local Ai

From Volume to Value: Preference-Aligned Memory Construction for On-Device RAG

arXiv:2605.18271v1 Announce Type: cross Abstract: With the rapid emergence of personal AI agents based on Large Language Models (LLMs), implementing them on-device has become essential for privacy and

local-aiarxiv-cs-ai

Full Attention Strikes Back: Transferring Full Attention into Sparse within Hundred Training Steps

arXiv:2605.16928v1 Announce Type: cross Abstract: Long-context inference in large language models is bottlenecked by the quadratic cost of full attention. Existing efficient alternatives often rely ei

researcharxiv-cs-ai

FUNCanon: Learning Pose-Aware Action Primitives via Functional Object Canonicalization for Generalizable Robotic Manipulation

arXiv:2509.19102v2 Announce Type: replace-cross Abstract: General-purpose robotic skills from end-to-end demonstrations often leads to task-specific policies that fail to generalize beyond the trainin

Function graph transformers universally approximate operators between function spaces

arXiv:2605.17968v1 Announce Type: new Abstract: We study the approximation of nonlinear operators between function spaces by transformers. Our approach is to lift functions to measures supported on th

Functionalization via Structure Completion and Motion Rectification

arXiv:2605.18010v1 Announce Type: new Abstract: Acquisition and creation of 3D assets have been largely view- or appearance-driven. As a result, existing digital 3D models often lack the requisite str

FUSE: A Framework for Unified State Estimation in Robotic SLAM Systems

arXiv:2605.18047v1 Announce Type: new Abstract: Tightly coupled SLAM formulations under mixed-rate sensing often bind temporal processing, local geometric association, estimator formulation, and map-u

safetyarxiv-cs-ro

GAMMA: Global Bit Allocation for Mixed-Precision Models under Arbitrary Budgets

arXiv:2605.18475v1 Announce Type: cross Abstract: Mixed-precision quantization improves the budget--accuracy trade-off for large language models (LLMs) by allocating more bits to sensitive modules. Ho

Gated KalmaNet: A Fading Memory Layer Through Test-Time Ridge Regression

model-releasesarxiv-cs-cl

arXiv:2511.21016v3 Announce Type: replace-cross Abstract: Linear State-Space Models (SSMs) offer an efficient alternative to softmax Attention with constant memory and linear compute, but their lossy,

GaussianDWM: 3D Gaussian Driving World Model for Unified Scene Understanding and Multi-Modal Generation

arXiv:2512.23180v3 Announce Type: replace Abstract: Driving World Models (DWMs) have been developing rapidly with the advances of generative models. However, existing DWMs lack 3D scene understanding

safetyarxiv-cs-cv

GaussianZoom: Progressive Zoom-in Generative 3D Gaussian Splatting with Geometric and Semantic Guidance

arXiv:2605.18252v1 Announce Type: new Abstract: We introduce GaussianZoom, a generative zoom-in 3D reconstruction system with an iterative progressive framework that combines geometry-consistent scene

GCE-MIL: Faithful and Recoverable Evidence for Multiple Instance Learning in Whole-Slide Imaging

arXiv:2605.17456v1 Announce Type: cross Abstract: Multiple instance learning (MIL) is the standard approach for whole-slide image (WSI) classification and survival prediction, where attention-based mo

researcharxiv-cs-ai

Agents

GEM: Gaussian Evolution Model for Occupancy Forecasting and Motion Planning

arXiv:2605.17682v1 Announce Type: new Abstract: Future 3D semantic occupancy forecasting and motion planning are central to autonomous driving, as they require models to reason about how surrounding s

agentsarxiv-cs-cv

General Preference Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2605.18721v1 Announce Type: cross Abstract: Post-training has split large language model (LLM) alignment into two largely disconnected tracks. Online reinforcement learning (RL) with verifiable

Generalizable and Actionable Parts Pose Estimation with Symmetry Annotation-Free Learning Strategy

arXiv:2605.17033v1 Announce Type: new Abstract: Urgently needed generalizable robot object interaction and manipulation requires high-quality Cross-Category object perception. As a pioneer of this are

researcharxiv-cs-ro

Generalization analysis with deep ReLU networks for metric and similarity learning

arXiv:2405.06415v2 Announce Type: replace-cross Abstract: While metric and similarity learning has been extensively studied from several theoretical perspectives, a rigorous understanding of its gener

Generalization or Memorization? Brittleness Testing for Chess-Trained Language Models

arXiv:2605.17565v1 Announce Type: new Abstract: Recent work has fine-tuned language models on chess data and reported high benchmark scores as evidence that the resulting models can understand the rul

Generalize cross-ratios in n-dimensional Plane-Based Geometric Algebra

arXiv:2605.18398v1 Announce Type: cross Abstract: We develop a complete theory of projective cross-ratios in n-dimensional Plane-Based Geometric Algebra (PGA), R(n,0,1), covering geometric objects of