model releases

Feature Rivalry in Sparse Autoencoder Representations: A Mechanistic Study of Uncertainty-Driven Feature Competition in LLMs

arXiv:2605.08149v1 Announce Type: cross Abstract: Sparse Autoencoders (SAEs) decompose large language model representations into interpretable features, but how these features interact under uncertain

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Featurized Occupation Measures for Structured Global Search in Numerical Optimal Control

DGX agent

arXiv:2603.16231v2 Announce Type: replace-cross Abstract: Numerical optimal control has long been split between globally structured but dimensionally intractable Hamilton--Jacobi--Bellman (HJB) method

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12 May 2026

Federated Language Models Under Bandwidth Budgets: Distillation Rates and Conformal Coverage

arXiv:2605.09986v1 Announce Type: cross Abstract: Training a language model on data scattered across bandwidth-limited nodes that cannot be centralized is a setting that arises in clinical networks, e

Filtering Memorization from Parameter-Space in Diffusion Models

arXiv:2605.10439v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) has become a widely used mechanism for customizing diffusion models, enabling users to inject new visual concepts or styles t

Fin-Bias: Comprehensive Evaluation for LLM Decision-Making under human bias in Finance Domain

arXiv:2605.09106v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in financial contexts, raising critical concerns about reliability, alignment, and susceptibility

FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting

arXiv:2502.18834v2 Announce Type: replace-cross Abstract: Financial time series (FinTS) record the behavior of human-brain-augmented decision-making, capturing valuable historical information that can

Fitting Multilinear Polynomials for Logic Gate Networks

arXiv:2605.08657v1 Announce Type: cross Abstract: We study learnable logic gate networks that stack layers of 2-input Boolean gates to build combinational circuits. Every 2-input gate has a unique mul

Fix the Loss, Not the Radius: Rethinking the Adversarial Perturbation of Sharpness-Aware Minimization

arXiv:2605.10183v1 Announce Type: new Abstract: Sharpness-Aware Minimization (SAM) improves generalization by minimizing the worst-case loss within a fixed parameter-space radius neighborhood. SAM and

FLAME: Adaptive Mixture-of-Experts for Continual Multimodal Multi-Task Learning

arXiv:2605.09355v1 Announce Type: new Abstract: Real-world model deployment across multiple domains requires multimodal models to operate under two complementary regimes: (1) multi-task pretraining, t

Flame3D: Zero-shot Compositional Reasoning of 3D Scenes with Agentic Language Models

arXiv:2605.09218v1 Announce Type: cross Abstract: 3D scene understanding spans reasoning about free space, object grounding, hypothetical object insertions, complex geometric relationships, and integr

FlashClear: Ultra-Fast Image Content Removal via Efficient Step Distillation and Feature Caching

arXiv:2605.09003v1 Announce Type: new Abstract: Recently, diffusion-based object removal models have achieved impressive results in eliminating objects and their associated visual effects. However, th

Follow the Mean: Reference-Guided Flow Matching

arXiv:2605.10302v1 Announce Type: new Abstract: Existing approaches to controllable generation typically rely on fine-tuning, auxiliary networks, or test-time search. We show that flow matching admits

Forge: Quality-Aware Reinforcement Learning for NP-Hard Optimization in LLMs

arXiv:2605.08905v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable success on reasoning benchmarks through Reinforcement Learning with Verifiable Rewards (RLVR), exc

FormalRewardBench: A Benchmark for Formal Theorem Proving Reward Models

arXiv:2605.10141v1 Announce Type: new Abstract: Recent neural theorem provers use reinforcement learning with verifiable rewards (RLVR), where proof assistants provide binary correctness signals. Whil

FORTIS: Benchmarking Over-Privilege in Agent Skills

arXiv:2605.09163v1 Announce Type: new Abstract: Large language model agents increasingly operate through an intermediate skill layer that mediates between user intent and concrete task execution. This

Four Over Six: More Accurate NVFP4 Quantization with Adaptive Block Scaling

arXiv:2512.02010v5 Announce Type: replace Abstract: As large language models have grown larger, interest has grown in low-precision numerical formats such as NVFP4 as a way to improve speed and reduce

FPGA-Based Hardware Architecture for Contrast Maximization in Event-Based Vision

arXiv:2605.09581v1 Announce Type: new Abstract: This paper presents a hardware architecture that implements the Contrast Maximization (CM) algorithm in Field-Programmable Gate Array (FPGA) resources f

FRACTAL: SSM with Fractional Recurrent Architecture for Computational Temporal Analysis of Long Sequences

arXiv:2605.08833v1 Announce Type: new Abstract: Effective sequence modeling fundamentally requires balancing the retention of unbounded history with the high-resolution detection of abrupt short-term

Frame In, Frame Out: Measuring Framing Bias in LLM-Generated News Summaries

arXiv:2505.05406v2 Announce Type: replace Abstract: News headlines and summaries shape how events are interpreted through selective emphasis and omission, a phenomenon commonly referred to as framing.

FraudBench: A Multimodal Benchmark for Detecting AI-Generated Fraudulent Refund Evidence

arXiv:2605.08820v1 Announce Type: cross Abstract: Artificial Intelligence (AI)-generated images have become increasingly realistic and readily adaptable to concrete real-world claims, creating new cha

FreeMOCA: Memory-Free Continual Learning for Malicious Code Analysis

arXiv:2605.09664v1 Announce Type: cross Abstract: As over 200 million new malware samples are identified each year, antivirus systems must continuously adapt to the evolving threat landscape. However,

From Articulated Kinematics to Routed Visual Control for Action-Conditioned Surgical Video Generation

arXiv:2605.08712v1 Announce Type: new Abstract: Action-conditioned surgical video generation is a critical yet highly challenging problem for robotic surgery. The core difficulty is that low-dimension

From Pixels to Concepts: Do Segmentation Models Understand What They Segment?

arXiv:2605.09591v1 Announce Type: new Abstract: Segmentation is a fundamental vision task underlying numerous downstream applications. Recent promptable segmentation models, such as Segment Anything M

From Traditional Taggers to LLMs: A Comparative Study of POS Tagging for Medieval Romance Languages

arXiv:2605.09147v1 Announce Type: cross Abstract: Part-of-speech (POS) tagging for Medieval Romance languages remains challenging due to orthographic variation, morphological complexity, and limited a

Function-Space ADMM for Decentralized Federated Learning: A Control Theoretic Perspective

arXiv:2605.09356v1 Announce Type: new Abstract: Decentralized federated learning (FL) is a promising approach for training machine learning models on sensor networks, Internet of Things (IoT) devices,

GAMBIT: A Three-Mode Benchmark for Adversarial Robustness in Multi-Agent LLM Collectives

arXiv:2605.09027v1 Announce Type: new Abstract: In multi-agent systems (MAS), a single deceptive agent can nullify all gains of an agentic AI collective and evade deployed defenses. However, existing

Gemini’s biggest new features are all about controlling your phone

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It is, once again, Gemini season. Google is announcing a host of new Gemini features during its pre-I/O Android showcase, many of which aim to help use your phone for you. You'll find Gemini in more p

General Agent Evaluation

arXiv:2602.22953v2 Announce Type: replace Abstract: General-purpose agents perform tasks in unfamiliar environments without domain-specific manual customization. Yet no study has systematically measur

Generating Leakage-Free Benchmarks for Robust RAG Evaluation

arXiv:2605.08838v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) is widely used to augment large language models (LLMs) with external knowledge. However, many benchmark datasets,

Generating Symmetric Materials using Latent Flow Matching

arXiv:2605.10115v1 Announce Type: new Abstract: Tackling the task of materials generation, we aim to enhance the previously proposed All-atom Diffusion Transformer (ADiT) by introducing SymADiT, a sym

Generative Actor-Critic with Soft Bridge Policies

arXiv:2605.08733v1 Announce Type: new Abstract: Expressive generative policies such as diffusion and flow models are appealing for MaxEnt online reinforcement learning because of their ability to mode

Generative AI Fuels Solo Entrepreneurship, but Teams Still Lead at the Top

arXiv:2605.10291v1 Announce Type: cross Abstract: Recent advances in generative artificial intelligence (AI) are reshaping who enters entrepreneurship, but not who reaches the top of the quality distr

GenMed: A Pairwise Generative Reformulation of Medical Diagnostic Tasks

arXiv:2605.10645v1 Announce Type: new Abstract: Data-driven medical AI is traditionally formulated as a discriminative mapping from input X to output Y via a learned function f, which does not general

Geometrically Constrained Stenosis Editing in Coronary Angiography via Entropic Optimal Transport

arXiv:2605.08851v1 Announce Type: cross Abstract: The scarcity of high-quality imaging data for coronary angiography (CAG) stenosis limits the clinical translation of automated stenosis detection. Syn

Geometry-Aware Discretization Error of Diffusion Models

arXiv:2605.08392v1 Announce Type: new Abstract: Practical diffusion sampling is a numerical approximation problem: under a fixed inference budget, one must simulate a reverse-time ODE or SDE using onl

Geometry Conflict: Explaining and Controlling Forgetting in LLM Continual Post-Training

arXiv:2605.09608v1 Announce Type: new Abstract: Continual post-training aims to extend large language models (LLMs) with new knowledge, skills, and behaviors, yet it remains unclear when sequential up

Geometry-free prediction of inertial lift forces in microfluidic devices using deep learning

arXiv:2605.08109v1 Announce Type: new Abstract: Inertial microfluidic devices (IMDs) offer low-cost, high-throughput alternative techniques for many traditional particle- (or cell-) manipulation tasks

Geospatial-Temporal Sensemaking of Remote Sensing Activity Detections with Multimodal Large Language Model

arXiv:2605.10739v1 Announce Type: cross Abstract: We introduce SMART-HC-VQA, a Sentinel-2-based visual question answering dataset derived from the IARPA SMART Heavy Construction dataset, designed for

GIFT: Guided Importance-Aware Fine-Tuning for Diffusion Language Models

arXiv:2509.20863v3 Announce Type: replace Abstract: Diffusion models have recently shown strong potential in language modeling, offering faster generation compared to traditional autoregressive approa

GLiNER-Relex: A Unified Framework for Joint Named Entity Recognition and Relation Extraction

arXiv:2605.10108v1 Announce Type: new Abstract: Joint named entity recognition (NER) and relation extraction (RE) is a fundamental task in natural language processing for constructing knowledge graphs

GLiNER2-PII: A Multilingual Model for Personally Identifiable Information Extraction

arXiv:2605.09973v1 Announce Type: cross Abstract: Reliable detection of personally identifiable information (PII) is increasingly important across modern data-processing systems, yet the task remains

Global Optimization via Softmin Energy Minimization

arXiv:2509.17815v2 Announce Type: replace Abstract: Global optimization, particularly for non-convex functions with multiple local minima, poses significant challenges for traditional gradient-based m

GONE: Structural Knowledge Unlearning via Neighborhood-Expanded Distribution Shaping

arXiv:2603.12275v1 Announce Type: cross Abstract: Unlearning knowledge is a pressing and challenging task in Large Language Models (LLMs) because of their unprecedented capability to memorize and dige

Google announces Gemini Intelligence, bundling existing and new Gemini features, including task automation across apps and vibe-coding own Android widgets (Allison Johnson/The Verge)

Allison Johnson / The Verge: Google announces Gemini Intelligence, bundling existing and new Gemini features, including task automation across apps and vibe-coding own Android widgets — We're one ste

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Google debuts Gemini Intelligence automation features, Googlebook laptop series

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Google LLC is upgrading its consumer device portfolio with a set of Android features called Gemini Intelligence and a new laptop series. The company debuted the products today during a virtual event c

Google DeepMind details a Gemini-powered mouse pointer that understands what it is pointing at, allowing users to perform tasks without using text-heavy prompts (Google DeepMind)

Google DeepMind: Google DeepMind details a Gemini-powered mouse pointer that understands what it is pointing at, allowing users to perform tasks without using text-heavy prompts — We are developing mo

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Google launches Intrusion Logging, an Android feature developed in partnership with Amnesty International and others, on Android 16 Pixel devices for now (Tim Starks/CyberScoop)

Tim Starks / CyberScoop: Google launches Intrusion Logging, an Android feature developed in partnership with Amnesty International and others, on Android 16 Pixel devices for now — Intrusion Logging m

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GraphBench: Next-generation graph learning benchmarking

arXiv:2512.04475v5 Announce Type: replace-cross Abstract: Machine learning on graphs has made substantial progress across domains such as molecular property prediction and chip design. Yet benchmarkin