Search: “models”

arXiv:2606.08375v1 Announce Type: new Abstract: All-atom generative modeling of 3D biomolecular complexes has emerged as the dominant paradigm for predicting the structure of proteins and protein-liga

safetyarxiv-cs-lg

Fluid, natural voice translation with Gemini 3.5 Live Translate

Gemini 3.5 Live Translate is an audio model delivering near real-time speech-to-speech translation in over 70 languages , with automatic language detection and natural-sounding translated speech that

model-releasesgoogle-deepmind

9 Jun 2026

Forecasting Japanese elections: A nonlinear machine-learning approach

arXiv:2606.07572v1 Announce Type: cross Abstract: Despite Japan being one of the world's largest advanced democracies, the development of election forecasting models for its national elections remains

From Statute to Control Flow: Span-Grounded Deontic Trees for Defeasible Scope Parsing

arXiv:2606.08932v1 Announce Type: cross Abstract: Rule-following agents tasked with executing policies and regulations often fail via Silent Scope Omission (SSO): a model applies a general rule but si

GEAR-VLA: Learning Geometry-Aware Action Representations for Generalizable Robotic Manipulation

arXiv:2606.08530v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models achieve strong benchmark performance but still struggle in real-world deployment with unseen objects, background s

Safety

Generalized Rank-based Evaluation for Knowledge Graph Completion: Perspectives, Framework, and Analyses

arXiv:2606.08921v1 Announce Type: new Abstract: Knowledge graph completion (KGC) aims to predict missing facts from an observed knowledge graph (KG), playing a crucial role in a wide range of real-wor

safetyarxiv-cs-lg

Harnessing Streaming Video in the Wild

arXiv:2606.08615v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are increasingly required to process unbounded video streams in applications such as video-call assistants, live commentar

Integrating Deep Learning Demand Forecasting with Multi-Objective Optimization for Circular Coffee Supply Chains: A Data-Driven Framework for Cost, Emissions, and Freshness Management

arXiv:2606.08314v1 Announce Type: new Abstract: The coffee supply chain is one of the most complex agri-food networks, marked by geographically dispersed production, multi-tier coordination, and high

Integrating gene regulatory priors into Transformer attention with scTransformer for interpretable scRNA-seq analysis

arXiv:2606.09558v1 Announce Type: cross Abstract: Motivation: Transformer-based models are increasingly applied to large-scale single-cell transcriptomics, showing strong performance through self-supe

Internalizing Geometric Law: Learning from Solver Residuals for Precision-Critical Generation

arXiv:2606.09278v1 Announce Type: cross Abstract: Large Language Models frequently hallucinate in precision-critical domains such as technical diagramming and mechanical design, where outputs must sat

Introducing the Fast Gemma Challenge with Hugging Face Over the next few days, dozens of agents will collaborate to make Gemma 4 E4B even fa…

model-releasesclem-delangue--x

Google and Hugging Face are launching the Fast Gemma Challenge, where multiple agents will collaborate to optimize the performance and speed of Gemma 4 E4B model. The initiative aims to improve the ef

KPGrasp: Scalable Keypoint Flow Matching for Dexterous Grasp Generation

model-releasesarxiv-cs-ro

arXiv:2606.09314v1 Announce Type: new Abstract: Generating high-quality dexterous grasps remains challenging for learning-based methods, which often depend on carefully tuned contact losses or costly

Learning Predictive Control with Deep Koopman Operators for Autonomous Vehicle Motion Planning

model-releasesarxiv-cs-ro

arXiv:2606.08136v1 Announce Type: new Abstract: Model Predictive Control (MPC) is widely used for autonomous-vehicle (AV) motion planning, but its real-time applicability is often limited by the need

Learning to Solve Generative ODEs Beyond the Linear Span

arXiv:2606.08672v1 Announce Type: new Abstract: Diffusion and flow generative models sample by integrating a learned ODE, but high quality still requires many sequential model evaluations. Solver lear

researcharxiv-cs-cv

LLM Inference at the Edge: Mobile, NPU, and GPU Performance Efficiency Trade-offs Under Sustained Load

arXiv:2603.23640v2 Announce Type: replace-cross Abstract: Deploying large language models on-device for always-on personal agents demands sustained inference from hardware tightly constrained in power

MEnvAgent: Scalable Polyglot Environment Construction for Verifiable Software Engineering

arXiv:2601.22859v3 Announce Type: replace-cross Abstract: The evolution of Large Language Model (LLM) agents for software engineering (SWE) is constrained by the scarcity of verifiable datasets, a bot

Minibatch Selection via Partition Matroid Constrained Gradient Matching

arXiv:2606.07954v1 Announce Type: cross Abstract: Training large language models (LLMs) on heterogeneous data requires selecting minibatches that balance convergence speed with coverage across domains

OmniGen-AR: AutoRegressive Any-to-Image Generation

arXiv:2606.09156v1 Announce Type: new Abstract: Autoregressive (AR) models have demonstrated strong potential in visual generation, offering superior performance with simple architectures and optimiza

OmniMem: Perturbation-aware Memory Compression for Streaming Audio-Visual LLMs

arXiv:2606.07577v1 Announce Type: new Abstract: Audio-visual large language models (LLMs) hold strong promise for long-form video understanding, yet their long-video inference is fundamentally limited

Partially Performative Prediction

arXiv:2606.07890v1 Announce Type: new Abstract: Performative prediction studies feedback loops that arise when predictive models are deployed in consequential domains. In these settings, deploying a m

Personalization Meets Safety:Mechanisms,Risks,and Mitigations in Personalized LLMs

arXiv:2606.09038v1 Announce Type: new Abstract: Large Language Models (LLMs) have enabled increasingly personalized interactions by adapting to users' preferences, contexts, and long-term histories. H

phepy: Visual benchmarks and improvements for out-of-distribution detectors

arXiv:2503.05169v2 Announce Type: replace Abstract: Applying machine learning to increasingly high-dimensional problems with sparse or biased training data increases the risk that a model is used on i

Pre-Intervention Prediction of Sparse Autoencoder Steering Side Effects

arXiv:2606.08365v1 Announce Type: cross Abstract: Sparse autoencoder (SAE) features are increasingly used to steer language models, but feature steering is rarely clean: the same intervention can beha

Read the blog to learn more: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-live-3-5-translate/

model-releasesgoogle-ai--x

This blog post from Google AI announces features and updates related to Gemini models, likely covering new capabilities for Gemini Live, version 3.5, and translation functionality. The announcement de

Revisiting Training Scale: An Empirical Study of Token Count, Power Consumption, and Parameter Efficiency

arXiv:2601.06649v2 Announce Type: replace-cross Abstract: Research in machine learning has questioned whether increases in training token counts reliably produce proportional performance gains in larg

SC3: The Multi-Solvent Solubility Challenge and Benchmark

arXiv:2606.07656v1 Announce Type: cross Abstract: Solubility prediction is a standard benchmark in computational chemistry, yet multi-solvent models which reportedly approach the experimental-noise ce

SciFlow-Bench: Evaluating Structure-Aware Scientific Diagram Generation via Inverse Parsing

arXiv:2602.09809v2 Announce Type: replace Abstract: Scientific diagrams convey explicit structural information, yet modern text-to-image models often produce visually plausible but structurally incorr

Local Ai

Self-Consistent Generative Paths via Admissible Random Variational Transport

arXiv:2606.08953v1 Announce Type: new Abstract: Modern generative models often define an entire probability path from a simple prior to the data law, rather than only an endpoint map. Diffusion models

local-aiarxiv-cs-lg

Shared Latent Structures Enable Unified Backdoor Detection and Mitigation in LLMs

arXiv:2606.07963v1 Announce Type: new Abstract: Backdoor attacks in large language models (LLMs) are often treated as isolated trigger-response failures, motivating defenses tailored to specific trigg

Shared Semantics, Divergent Mechanisms: Unsupervised Feature Discovery by Aligning Semantics and Mechanisms

arXiv:2606.08236v1 Announce Type: cross Abstract: As large language models are increasingly deployed in high-stakes settings, there is a growing need for tools that audit not only model outputs but al

SNN-MLIR: An MLIR Dialect for Compiling Neuromorphic SNNs from NIR to Bare-Metal C

arXiv:2606.09213v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) are increasingly trained in a wide range of frameworks (SnnTorch, Lava, Norse, and others) each with its own model form

Sovereign AI for all.

Cohere advocates for democratizing access to sovereign AI systems, enabling organizations and nations to develop and deploy their own AI models independently rather than relying on centralized provide

model-releasescohere--x

SpectrumKV: Per-Token Mixed-Precision KV Cache Transfer for Prefill-Decode Disaggregated LLM Serving

arXiv:2606.08635v1 Announce Type: new Abstract: Prefill-decode (PD) disaggregation decouples prompt processing from token generation, but it also turns the key-value (KV) cache into a network payload.

Safety

Steganography Without Modification: Hidden Communication via LLM Seeds

arXiv:2606.09135v1 Announce Type: cross Abstract: We demonstrate that widely deployed Large Language Model (LLM) inference stacks harbor a steganographic channel that requires no modification to model

safetyarxiv-cs-ai

Struct-Searcher: Agentic Structural Thinking Advances Multimodal Deep Information Seeking

arXiv:2606.07689v1 Announce Type: new Abstract: Deep research agents have attracted increasing attention for their ability to collect large-scale online information to acquire target knowledge, with r

The Injection Paradox: Brand-Level Suppression in Safety-Trained LLM Recommendations via RAG Context Injection

arXiv:2606.09204v1 Announce Type: new Abstract: We present a reproducible failure mode of safety training in RAG-based LLM recommendation -- the Injection Paradox -- in which prompt injections embedde

The Mirrored Influence Hypothesis: Efficient Data Influence Estimation by Harnessing Forward Passes

arXiv:2402.08922v3 Announce Type: replace Abstract: Large-scale black-box models have become ubiquitous across numerous applications. Understanding the influence of individual training data sources on

There has been a lot of hand wringing on the appropriate valuation of SpaceX. Some large institutions believe SpaceX can only be valued at h…

model-releaseselon-musk--x

There has been a lot of hand wringing on the appropriate valuation of SpaceX. Some large institutions believe SpaceX can only be valued at half what the market seems to be willing to pay for it. Other

TQA-Bench: Evaluating LLMs for Multi-Table Question Answering

arXiv:2411.19504v2 Announce Type: replace Abstract: The advance of large language models (LLMs) has unlocked great opportunities in complex multi-modal data management tasks, particularly in question

TRL-Bench: Standardizing Cross-Paradigm Representation-Level Evaluation of Tabular Encoders

arXiv:2606.09323v1 Announce Type: new Abstract: Tabular encoders are usually evaluated inside task-specific end-to-end pipelines, so models from different training paradigms are difficult to compare d

Unification of Closed-Open Industrial Detection Scenarios: New Large-Scale Benchmarks,Challenges and Baselines

arXiv:2606.07953v1 Announce Type: new Abstract: Large-scale Visual-Language Models (LVLMs) have achieved remarkable success in natural visual tasks, yet their application to industrial defect detectio

UniQL: Towards Dialect-Universal Benchmarking for Text-to-SQL

arXiv:2606.08018v1 Announce Type: new Abstract: Existing text-to-SQL benchmarks are largely centered on SQLite, making it difficult to evaluate whether models can generalize across heterogeneous SQL d

VFEM: Visual Feature Empowered Multivariate Time Series Forecasting with Cross-Modal Fusion

arXiv:2510.03244v2 Announce Type: replace-cross Abstract: Large time series foundation models often adopt channel-independent architectures to handle varying data dimensions, but this design ignores c

researcharxiv-cs-ai

We've got 13 days to burn as much tokens as humanly possible on Claude Max plans Before they revert to API based billing 💀

model-releasesjerry-liu--x

We've got 13 days to burn as much tokens as humanly possible on Claude Max plans Before they revert to API based billing 💀 Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for gen

A Geometric Gaussian Mixture Representation of Plane Curves

arXiv:2606.06505v1 Announce Type: cross Abstract: We introduce a user defined probabilistic polygonal representation for plane curves. Given a curve, we select vertices on the curve and connect consec

Act As a Real Researcher: A Suite of Benchmarks Evaluating Frontier LLMs and Agentic Harnesses in Research Lifecycle

arXiv:2606.07462v1 Announce Type: new Abstract: As foundation models advance and agent scaffolding becomes increasingly sophisticated, agents have demonstrated remarkable proficiency in complex, long-

From Sampled Outcomes to Capability Distributions: Rethinking Supervision for LLM Routing

arXiv:2606.06924v1 Announce Type: new Abstract: Existing LLM routing methods typically treat a model's single response to a query as its capability label for training routers. However, because LLM gen

Generative Molecular Morphing for Flexible-Size Design via Unbalanced Optimal Transport

arXiv:2606.07239v1 Announce Type: new Abstract: The success of generative molecular design hinges on a model's steerability toward high-reward samples. Because many molecular properties are intrinsica