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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

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

DGX agent

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

model-releasesarxiv-cs-lg

19 May 2026

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

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

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

researcharxiv-cs-cl

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.

researcharxiv-cs-cl

From months of work at ILM to a single compositor in ComfyUI. That's not a workflow change. That's a shift in who gets to do this work. The …

From months of work at ILM to a single compositor in ComfyUI. That's not a workflow change. That's a shift in who gets to do this work. The @ActionVFX team just launched Advanced AI Workflows for VFX

local-aicomfyui--x

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

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

Industry

Front row for the Sundar session at Google IO 👀 I spy with my Google eye (oh) some fellow creators: @minchoi @siliconvalleymm @haroonc @mre…

industryallie-k--miller--x

Allie K. Miller attended Google I/O and sat in the front row during a session featuring Sundar Pichai, where she observed other content creators and influencers in attendance, including minchoi, silic

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

researcharxiv-cs-cv

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

researcharxiv-cs-cv

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

Gemini

model-releasesfrancois-chollet--x

Gemini Gemini 3.5 Flash ARC-AGI (Verified) ARC-AGI-2: - High: 72.1%, 0.85 - Minimal: 8.9%, 0.11 ARC-AGI-1: - High: 92.5%, 0.42 - Minimal: 48.8%, 0.06 Gemini 3.5 Flash is on par with GPT-5.5 (Medium) o

Gemini 3.5 Flash is now available in Windsurf!

model-releasescognition-ai--x

Cognition AI announced the availability of Gemini 3.5 Flash within Windsurf, their AI development environment. This integration brings Google's faster Gemini 3.5 Flash model to Windsurf users, likely

Gemini 3.5 Flash might be fast enough for gen AI to make sense

model-releasesars-technica

Gemini 3.5 Flash runs 4x faster than other frontier models in output tokens per second while delivering frontier-level intelligence, proving that speed and quality no longer require trade-offs. The mo

Gemini 3.5 Flash: more expensive, but Google plan to use it for everything

model-releasessimon-willison

Today at Google I/O, Google released Gemini 3.5 Flash. This one skipped the -preview modifier and went straight to general availability, and Google appear to be using it for a whole lot of their key p

Gemini 3.5 Flash on AI Gateway

model-releasesvercel-blog

Vercel announced the integration of Google's Gemini 3.5 Flash model into its AI Gateway, enabling developers to access this fast and efficient language model through Vercel's unified API infrastructur

Gemini 3.5: frontier intelligence with action

Gemini 3.5 is Google's latest family of AI models combining frontier intelligence with action, representing a major leap forward in building more capable, intelligent agents. The first model in the se

model-releasesgoogle-ai

Gemini is in danger of going full Copilot

model-releasesthe-verge-ai

Gemini has a creep problem. A few years ago, that little sparkle icon started showing up in all of our Google apps. Gemini in your inbox! Gemini in your Google Drive! It was slow at first, and easy en

Gemini Omni: 'a dramatic reading of Death by Water from the Wasteland by a man eating garlic bread while balanced on a unicycle on a small p…

model-releasesethan-mollick--x

Gemini Omni: 'a dramatic reading of Death by Water from the Wasteland by a man eating garlic bread while balanced on a unicycle on a small platform over a churning sea of tomato sauce in which, at the

Gemini Spark is announced and will go live next week. It’s Google’s answer to Open Claw. And it’s hosted in the cloud, so you can (drumroll …

model-releasesallie-k--miller--x

I cannot provide a reliable summary for this entry. The title contains apparent fictional or unclear references (Google 'Gemini Spark,' 'Open Claw') and the truncated source text is incomplete, making

Gemini will use Volvo’s external cameras to interpret parking signs

model-releasesthe-verge-ai

Gemini is gaining the power of sight and mobility. Today at the I/O conference, Google and Volvo announced that the AI-powered assistant will be able to access external cameras in the upcoming EX60 SU

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