Search: “models”

Beyond Bounded Variance: Variance-Reduced Normalized Methods for Nonconvex Optimization under Blum-Gladyshev Noise

arXiv:2605.15314v1 Announce Type: new Abstract: We study nonconvex stochastic optimization under the Blum-Gladyshev (mathsf{BG}-0) noise model, where the stochastic gradient variance grows quadratical

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BiomedAP: A Vision-Informed Dual-Anchor Framework with Gated Cross-Modal Fusion for Robust Medical Vision-Language Adaptation

DGX agent

arXiv:2605.15736v1 Announce Type: cross Abstract: Biomedical Vision--Language Models (VLMs) have shown remarkable promise in few-shot medical diagnosis but face a critical bottleneck: extit{fragility

model-releasesarxiv-cs-ai

18 May 2026

Can We Trust AI-Inferred User States. A Psychometric Framework for Validating the Reliability of Users States Classification by LLMs in Operational Environments

arXiv:2605.15734v1 Announce Type: new Abstract: The use of large language models to assess user states in conversational and adaptive systems is based on the assumption that the metrics used for such

COPRA: Conditional Parameter Adaptation with Reinforcement Learning for Video Anomaly Detection

arXiv:2605.15325v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown strong performance in video anomaly detection (VAD) while providing interpretable predictions. However, existin

ElasticDiT: Efficient Diffusion Transformers via Elastic Architecture and Sparse Attention for High-Resolution Image Generation on Mobile Devices

arXiv:2605.15684v1 Announce Type: new Abstract: The Diffusion Transformer (DiT) architecture is the state-of-the-art paradigm for high-fidelity image generation, underpinning models like Stable Diffus

safetyarxiv-cs-cv

Fully Open Meditron: An Auditable Pipeline for Clinical LLMs

arXiv:2605.16215v1 Announce Type: new Abstract: Clinical decision support systems (CDSS) require scrutable, auditable pipelines that enable rigorous, reproducible validation. Yet current LLM-based CDS

Research

GenAI-Driven Approach to RISC-V Supply Chain Exploration

arXiv:2605.15223v1 Announce Type: cross Abstract: This paper presents an LLM-empowered workflow for RISC-V supply chain analysis, integrating Vision-Language Models (VLMs) and Model-Driven Engineering

researcharxiv-cs-ai

Harnessing Unimodality in Semiparametric Contextual Pricing via Oracle Price Map Learning

arXiv:2605.15411v1 Announce Type: cross Abstract: We study contextual dynamic pricing in a semiparametric scalar-index valuation model where the latent value is v_t=mu_ast(mathsf c_t)+xi_t, with an un

Hidden in Memory: Sleeper Memory Poisoning in LLM Agents

arXiv:2605.15338v1 Announce Type: cross Abstract: Large language models are increasingly augmented with persistent memory, allowing assistants to store user-specific information across sessions for pe

IndicSafe: A Benchmark for Evaluating Multilingual LLM Safety in South Asia

arXiv:2603.17915v2 Announce Type: replace-cross Abstract: As large language models (LLMs) are deployed in multilingual settings, their safety behavior in culturally diverse, low-resource languages rem

LoCO: Low-rank Compositional Rotation Fine-tuning

arXiv:2605.15916v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) has emerged as an critical technique for adapting large-scale foundation models across natural language process

MorphoHELM: A Comprehensive Benchmark for Evaluating Representations for Microscopy-Based Morphology Assays

arXiv:2605.15383v1 Announce Type: new Abstract: Microscopy images contain rich information about how cells respond to perturbations, making them essential to applications like drug screening. To quant

Njord: A Probabilistic Graph Neural Network for Ensemble Ocean Forecasting

arXiv:2605.15470v1 Announce Type: new Abstract: Ocean dynamics are inherently chaotic, yet existing machine learning ocean models produce only deterministic forecasts. We introduce Njord, a probabilis

PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control

arXiv:2605.15963v1 Announce Type: new Abstract: Large vision-language models have significantly advanced GUI agents, enabling executable interaction across web, mobile, and desktop interfaces. Yet the

Applications

Process-Informed Forecasting of Complex Thermal Dynamics in Pharmaceutical Manufacturing

arXiv:2509.20349v3 Announce Type: replace Abstract: Accurate time-series forecasting for complex physical systems is the backbone of modern industrial monitoring and control, yet deep learning models

applicationsarxiv-cs-lg

Quantum Feature Pyramid Gating for Seismic Image Segmentation

arXiv:2605.15370v1 Announce Type: cross Abstract: Accurate salt-body delineation is essential for seismic interpretation because salt structures distort wave propagation, complicate velocity-model bui

SaaS-Bench: Can Computer-Use Agents Leverage Real-World SaaS to Solve Professional Workflows?

arXiv:2605.15777v1 Announce Type: new Abstract: Computer-Using Agents (CUAs) are rapidly extending large language models (LLMs) beyond text-based reasoning toward action execution in more complex envi

Local Ai

Sound Sparks Motion: Audio and Text Tuning for Video Editing

arXiv:2605.15307v1 Announce Type: cross Abstract: Motion-centric video editing remains difficult for large generative video models, which often respond well to appearance changes but struggle to produ

local-aiarxiv-cs-cv

Structure-BiEval: A Self-Supervised, Dual-Track Framework for Decoupling Structure and Content in LLM Evaluation for Web Information Systems

arXiv:2601.19923v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) evolve into the core of Web-based autonomous agents and complex Web Information Systems, their ability to fait

SynthRender and IRIS: Open-Source Framework and Dataset for Bidirectional Sim-Real Transfer in Industrial Object Perception

arXiv:2602.21141v2 Announce Type: replace Abstract: Object perception is fundamental for tasks such as robotic material handling and quality inspection. However, modern supervised deep-learning models

Agents

Talking Trees: Reasoning-Assisted Induction of Decision Trees for Tabular Data

arXiv:2509.21465v3 Announce Type: replace Abstract: Tabular foundation models are becoming increasingly popular for low-resource tabular problems. These models make up for small training datasets by p

agentsarxiv-cs-lg

TokenButler: Token Importance is Predictable

arXiv:2503.07518v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) rely on the Key-Value (KV) Cache to store token history, enabling efficient decoding of tokens. As the KV-Cache g

What we announced in streaming AI at Next ‘26

model-releasesgoogle-cloud-ai

Every device, user, and microservice generates data. Ingesting this data, extracting meaning and insights, and driving business decisions in real time has the potential to deliver transformational bus

G4-MeroMero-31B-uncensored-heretic is Out Now, A finetune of Gemma 4 31B it designed for creative tasks, with KLD of 0.0100 and 15/100 Refusals!

G4-MeroMero-31B-uncensored-heretic is a fine-tuned variant of Gemma 4 31B optimized for creative tasks, featuring low KL divergence (0.0100) and minimal refusals (15/100). The model is designed to be

model-releasesr-ollama

17 May 2026

Introducing Gemini Omni

model-releasesgoogle-deepmind

Gemini Omni is a multimodal AI model that allows users to create content from any input and edit naturally using conversational language . Users can combine images, audio, video, and text as input to

17 May 2026

Recent Developments in LLM Architectures: KV Sharing, mHC, and Compressed Attention

model-releasessebastian-raschka

This article discusses recent advancements in large language model architecture design, focusing on key-value (KV) sharing techniques, multi-head cache (mHC) mechanisms, and compressed attention metho

16 May 2026

ACE-LoRA: Adaptive Orthogonal Decoupling for Continual Image Editing

arXiv:2605.14948v1 Announce Type: new Abstract: State-of-the-art diffusion models often rely on parameter-efficient fine-tuning to perform specialized image editing tasks. However, real-world applicat

ArGEnT: Arbitrary Geometry-encoded Transformer for Operator Learning

arXiv:2602.11626v2 Announce Type: replace-cross Abstract: Learning solution operators for systems with complex, varying geometries and parametric physical settings is a central challenge in scientific

AttnGen: Attention-Guided Saliency Learning for Interpretable Genomic Sequence Classification

arXiv:2605.14073v1 Announce Type: cross Abstract: Deep neural networks have achieved strong performance in genomic sequence classification; however, relating their predictions to biologically meaningf

Research

CC-Pan: Channel-wise Compression based Diffusion for Efficient Pan-Sharpening

arXiv:2602.04473v2 Announce Type: replace Abstract: Recently, diffusion models have brought novel insights to pan-sharpening and notably boosted fusion precision. However, most existing models perform

researcharxiv-cs-cv

CurveBench: A Benchmark for Exact Topological Reasoning over Nested Jordan Curves

arXiv:2605.14068v1 Announce Type: new Abstract: We introduce CurveBench, a benchmark for hierarchical topological reasoning from visual input. CurveBench consists of extbf{756 images} of pairwise non-

Databricks brings GPT-5.5 to enterprise agent workflows

Databricks has integrated OpenAI's GPT-5.5 model into enterprise agent workflows, enabling organizations to build and deploy AI agents with advanced language capabilities. This partnership leverages D

model-releasesopenai

Derivation Prompting: A Logic-Based Method for Improving Retrieval-Augmented Generation

arXiv:2605.14053v1 Announce Type: cross Abstract: The application of Large Language Models to Question Answering has shown great promise, but important challenges such as hallucinations and erroneous

Does RAG Know When Retrieval Is Wrong? Diagnosing Context Compliance under Knowledge Conflict

arXiv:2605.14473v1 Announce Type: cross Abstract: The Context-Compliance Regime in Retrieval-Augmented Generation (RAG) occurs when retrieved context dominates the final answer even when it conflicts

Exemplar Partitioning for Mechanistic Interpretability

arXiv:2605.14347v1 Announce Type: new Abstract: We introduce Exemplar Partitioning (EP), an unsupervised method for constructing interpretable feature dictionaries from large language model activation

FlowInOne:Unifying Multimodal Generation as Image-in, Image-out Flow Matching

arXiv:2604.06757v2 Announce Type: replace Abstract: Multimodal generation has long been dominated by text-driven pipelines where language dictates vision but cannot reason or create within it. We chal

Fusion-fission forecasts when AI will shift to undesirable behavior

arXiv:2605.14218v1 Announce Type: new Abstract: The key problem facing ChatGPT-like AI's use across society is that its behavior can shift, unnoticed, from desirable to undesirable -- encouraging self

GenExam: A Multidisciplinary Text-to-Image Exam

arXiv:2509.14232v5 Announce Type: replace Abstract: Exams are a fundamental test of expert-level intelligence and require integrated understanding, reasoning, and generation. Existing exam-style bench

GPart: End-to-End Isometric Fine-Tuning via Global Parameter Partitioning

arXiv:2605.14841v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) has become the dominant paradigm for parameter-efficient fine-tuning (PEFT) of large language models (LLMs). However, its b

GradShield: Alignment Preserving Finetuning

arXiv:2605.14194v1 Announce Type: new Abstract: Large Language Models (LLMs) pose a significant risk of safety misalignment after finetuning, as models can be compromised by both explicitly and implic

safetyarxiv-cs-cl

GroupMemBench: Benchmarking LLM Agent Memory in Multi-Party Conversations

model-releasesarxiv-cs-cl

arXiv:2605.14498v1 Announce Type: new Abstract: Large Language Model (LLM) agents increasingly serve as personal assistants and workplace collaborators, where their utility depends on memory systems t

How data science teams use Codex

This OpenAI Academy resource explores practical applications of Codex, their AI code generation model, within data science workflows and teams. It likely covers how data scientists leverage Codex to a

model-releasesopenai

IPR-1: Interactive Physical Reasoner

arXiv:2511.15407v3 Announce Type: replace Abstract: Humans learn by observing, interacting with environments, and internalizing physics and causality. Here, we aim to ask whether an agent can similarl

Learning to Build the Environment: Self-Evolving Reasoning RL via Verifiable Environment Synthesis

arXiv:2605.14392v1 Announce Type: new Abstract: We pursue a vision for self-improving language models in which the model does not merely generate problems or traces to imitate, but constructs the envi

safetyarxiv-cs-ai

LoRA in LoRA: Towards Parameter-Efficient Architecture Expansion for Continual Visual Instruction Tuning

arXiv:2508.06202v2 Announce Type: replace-cross Abstract: Continual Visual Instruction Tuning (CVIT) enables Multimodal Large Language Models (MLLMs) to incrementally learn new tasks over time. Howeve

Agents

MALLVI: A Multi-Agent Framework for Integrated Generalized Robotics Manipulation

arXiv:2602.16898v5 Announce Type: replace-cross Abstract: Task planning for robotic manipulation with large language models (LLMs) is an emerging area. Prior approaches rely on specialized models, fin

agentsarxiv-cs-ai

Mechanical Enforcement for LLM Governance:Evidence of Governance-Task Decoupling in Financial Decision Systems

arXiv:2605.14744v1 Announce Type: cross Abstract: Large language models in regulated financial workflows are governed by natural-language policies that the same model interprets, creating a principal-

safetyarxiv-cs-ai

Local Ai

Mistletoe: Stealthy Acceleration-Collapse Attacks on Speculative Decoding

arXiv:2605.14005v1 Announce Type: new Abstract: Speculative decoding has become a widely adopted technique for accelerating large language model (LLM) inference by drafting multiple candidate tokens a

local-aiarxiv-cs-cl