Search: “model-releases”

iSAGE: A Human-in-the-Loop Framework for Remote Sensing Semantic Segmentation via Sparse Point Supervision

arXiv:2606.10136v1 Announce Type: new Abstract: Semantic segmentation in remote sensing requires costly pixel-level annotations, and nearly every problem demands a new dataset since models rarely tran

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Janus: A Benchmark for Goal-Conditioned Information Distortion in LLMs

DGX agent

arXiv:2606.10852v1 Announce Type: cross Abstract: LLM deception is often evaluated through direct markers such as fabricated claims, explicit lies, or strategic concealment. However, many real-world m

model-releasesarxiv-cs-ai

10 Jun 2026

JGRA: Jacobian Geometry Robustness Assessment in NISQ Noise-Aware Quantum Neural Networks

arXiv:2606.09964v1 Announce Type: cross Abstract: The NISQ era places stringent constraints on quantum computation, where noise and decoherence fundamentally limit performance. In classical deep learn

KCSAT-ML: Probing Reasoning Models with Nationwide-Cohort Human Difficulty

arXiv:2606.10403v1 Announce Type: new Abstract: Math reasoning benchmarks have proliferated, yet most lack a per-item difficulty signal grounded in actual human performance. We introduce KCSAT-ML, a d

Kwai Keye-VL-2.0 Technical Report

arXiv:2606.10651v1 Announce Type: new Abstract: We introduce Kwai Keye-VL-2.0-30B-A3B, an open-source Mixture-of-Experts (MoE) multimodal foundation model designed to advance long-video understanding

LakeQA: An Exploratory QA Benchmark over a Million-Scale Data Lake

arXiv:2606.10460v1 Announce Type: cross Abstract: Recent large language models (LLMs) have shown rapid progress in reading-based question answering (QA), where evidence is explicitly provided or can b

Latent Guided Sampling for Combinatorial Optimization

arXiv:2506.03672v2 Announce Type: replace-cross Abstract: Combinatorial Optimization problems are widespread in domains such as logistics, manufacturing, and drug discovery, yet their NP-hard nature m

Less Context, Better Agents: Efficient Context Engineering for Long-Horizon Tool-Using LLM Agents

arXiv:2606.10209v1 Announce Type: new Abstract: Large language models deployed as autonomous agents for enterprise workflows face a key challenge: verbose tool responses from enterprise systems can ca

Less Context, More Accuracy: A Bi-Temporal Memory Engine for LLM Agents Where a Lean Retrieved Context Beats the Full History

arXiv:2606.09900v1 Announce Type: cross Abstract: Long-term memory is the missing layer for LLM agents: across sessions they forget, and the common workaround -- replaying the whole history into the p

Letter: Texas Governor Greg Abbott released regulatory recommendations for state lawmakers to ensure that data centers shoulder the costs of their growth (The Texas Tribune)

The Texas Tribune: Letter: Texas Governor Greg Abbott released regulatory recommendations for state lawmakers to ensure that data centers shoulder the costs of their growth — The recommendations for l

model-releasestechmeme

LIBERO-Occ: Evaluating and Improving Vision-Language-Action Models under Scene-Induced Occlusion via Viewpoint Imagination

arXiv:2606.10862v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models achieve strong performance on standard manipulation benchmarks, but most evaluations assume that task-relevant obj

LLM-as-a-Discriminator: When Synthetic Tables Still Look Real

arXiv:2606.09865v1 Announce Type: new Abstract: Privacy and data sharing are often in tension. Many organizations use synthetic data to reduce privacy risk and still share useful data. For tabular dat

LLM-Based Code Documentation Generation and Multi-Judge Evaluation

arXiv:2606.09852v1 Announce Type: cross Abstract: High-quality source code documentation is vital yet often neglected, especially in critical domains like healthcare where reliability and maintainabil

Local Is Not a Sufficient Privacy Boundary: Governing OS-Integrated On-Device AI

arXiv:2606.10173v1 Announce Type: cross Abstract: As AI systems move into operating systems, privacy no longer turns only on whether a model runs locally. A local assistant may assemble email, calenda

Magnetic HIP-NN for spin dynamics in disordered itinerant magnets

arXiv:2606.10349v1 Announce Type: cross Abstract: We present a magnetic extension of the Hierarchically Interacting Particle Neural Network (HIP-NN) that enables large-scale simulations of electron-me

Me, 2024. LLMs will be commodity; (except for Nvdia) profits will be hard to squeeze out. Techbros: Shut up, Gary. GPT-5 is gonna be AGI. To…

model-releasesgary-marcus--x

Me, 2024. LLMs will be commodity; (except for Nvdia) profits will be hard to squeeze out. Techbros: Shut up, Gary. GPT-5 is gonna be AGI. Today: LLMs are commodity; (except for Nvidia) profits have be

Meet DiffusionGemma! An experimental open model that explores a fast approach to text generation, released under an Apache 2.0 license. Movi…

model-releasesclem-delangue--x

Meet DiffusionGemma! An experimental open model that explores a fast approach to text generation, released under an Apache 2.0 license. Moving beyond sequential, token-by-token processes to generate e

MemVenom: Triggered Poisoning of Multimodal Memories in Web Agents

arXiv:2606.10742v1 Announce Type: cross Abstract: External memory has become a core component of modern web agents, enabling long-horizon reasoning through the retrieval of past experiences. However,

Microsoft restricts Claude Fable for employees over data retention concerns

model-releasesthe-verge-ai

Anthropic released Claude Fable, its first Mythos-class AI model, yesterday and it's already causing concerns inside Microsoft. Sources tell me that Microsoft is limiting the use of Claude Fable 5 for

Mind the Gap: Can Frontier LLMs Pass a Standardized Office Proficiency Exam?

arXiv:2606.10956v1 Announce Type: new Abstract: The deployment of Large Language Model (LLM) agents for computer automation is accelerating, yet their ability to navigate complex, professional-grade p

MIRAGE: A Polarity-Flipping Encoding Subspace in LLM Agents

arXiv:2606.10304v1 Announce Type: new Abstract: When LLM agents are coerced into covertly encoding sensitive data (Base64, ROT13, acrostic, synonym chains, and beyond), the resulting outputs evade out

Mixtures of Neural Operators Reduce Active Complexity in Operator Learning

arXiv:2404.09101v3 Announce Type: replace-cross Abstract: Operator-learning systems are not governed solely by total parameter count; for one query, the relevant bottleneck can be the model that must

mlr3mbo: Bayesian Optimization in R

arXiv:2603.29730v2 Announce Type: replace-cross Abstract: We present mlr3mbo, a modular toolbox for Bayesian optimization in R. mlr3mbo supports single- and multi-objective optimization, multi-point p

MMClima: A Framework for Multimodal Climate Science Data and Evaluation

arXiv:2606.10194v1 Announce Type: cross Abstract: Climate change research increasingly requires AI systems that reason across text, dynamic visual content, and scientific figures, yet existing climate

Modeling Complex Behaviors: Multi-Personality Composition and Dynamic Switching in Vision-Language Models

arXiv:2606.11074v1 Announce Type: cross Abstract: With the widespread deployment of Multimodal Large Language Models (MLLMs) in social interaction, understanding and controlling their behavior under c

MoE Enhanced Federated Learning for Spatiotemporal Prediction

arXiv:2606.10499v1 Announce Type: cross Abstract: Traffic prediction is fundamental to intelligent transportation systems and urban computing, yet many cities continue to suffer from traffic data scar

Monte Carlo Pass Search: Using Trajectory Generation for 3D Counterfactual Pass Evaluation in Football

arXiv:2606.11120v1 Announce Type: new Abstract: We recast pass evaluation in football (soccer) as a Monte Carlo Tree Search (MCTS)-like evaluation problem whose components mostly exist in the literatu

Moonshine: An Autonomous Mathematical Research Agent Centered on Conjecture Generation

arXiv:2606.10806v1 Announce Type: new Abstract: Moonshine is an autonomous agent whose central objective is to generate mathematical conjectures. Its core capability is to extract structure from class

MV-Actor: Aligning Multi-View Semantics and Spatial Awareness for Bimanual Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.10899v1 Announce Type: new Abstract: Robotic manipulation has been widely applied in industrial scenarios. Compared with single-arm manipulation, bimanual manipulation is equipped with mult

N-GRPO: Embedding-Level Neighbor Mixing for Enhanced Policy Optimization

arXiv:2606.10768v1 Announce Type: cross Abstract: The success of Large Language Models in mathematical reasoning relies heavily on the generation of diverse and valid solution paths during the rollout

nCMD: Benign-Anchored Feature Selection for Imbalanced Network Intrusion Detection

arXiv:2606.09934v1 Announce Type: new Abstract: Feature selection is critical for network intrusion detection systems (NIDS) operating under high-dimensional, highly imbalanced traffic, as found in op

Next Forcing: Causal World Modeling with Multi-Chunk Prediction

arXiv:2606.11187v1 Announce Type: new Abstract: Autoregressive video generation has emerged as a powerful paradigm for World Action Models (WAMs). However, existing approaches suffer from slow trainin

Non-Parametric Structural Priors for Geometry Theorem Prediction

arXiv:2603.04852v2 Announce Type: replace Abstract: Multi-step theorem prediction is a central challenge in geometry problem solving. Existing neural-symbolic approaches rely heavily on supervised par

Nonlinear Estimator: Dual Bayesian Affine Estimators for Parameter Learning

arXiv:2606.10111v1 Announce Type: new Abstract: This paper presents a nonlinear parameter estimator for Wiener-type state-space models obtained as a fixed-point architecture that couples two affine mi

NOVA: Symbolic Regression Discovery of Interpretable Car-Following and Lane-Change Models with Driver Heterogeneity

arXiv:2606.10583v1 Announce Type: cross Abstract: We present NOVA, an autonomous symbolic regression framework that identifies interpretable car-following and lane-change structures from raw trajector

NVIDIA Accelerates Google DeepMind’s DiffusionGemma for Local AI

model-releasesnvidia-blog

Today, Google DeepMind released DiffusionGemma — an experimental open model built for exceptionally fast text generation. NVIDIA has optimized DiffusionGemma to run even faster across NVIDIA GeForce R

OncoTraj: a public benchmark for longitudinal resistance prediction in EGFR-mutant non-small-cell lung cancer on osimertinib

arXiv:2606.11144v1 Announce Type: new Abstract: Resistance to first-line osimertinib in EGFR-mutant non-small-cell lung cancer (NSCLC) is the canonical example of predictable clonal evolution under th

One Step Closer to Ground Truth: A Multi-Scale Residual-Aware Representation Learning Pipeline for Predicting Time Series Data

arXiv:2606.10678v1 Announce Type: new Abstract: Transformer-based models have emerged as leading paradigms in time-series forecasting in recent years, employing self-attention mechanisms to capture lo

Online Self-Training for Co-Adaptation in Hierarchical Diffusion Policies

model-releasesarxiv-cs-ro

arXiv:2603.05291v2 Announce Type: replace Abstract: Hierarchical policies decompose language-conditioned long-horizon robotic manipulation into a high-level planner and a low-level controller. However

OpenRTLSet: A Fully Open-Source Dataset for Large Language Model-based Verilog Module Design

arXiv:2606.10285v1 Announce Type: new Abstract: OpenRTLSet introduces the largest fully open-source dataset for hardware design, offering over 131,000 diverse Verilog code samples to the research comm

Optimal Post-Training Quantization Scales and Where to Find Them

arXiv:2606.10890v1 Announce Type: cross Abstract: Post-training quantization (PTQ) compresses large language models by mapping weights to low-bit representations. The scaling factor that defines the q

Optimization-based Online Conformal Prediction for Multi-step Forecasting

arXiv:2508.13362v2 Announce Type: replace Abstract: Conformal prediction (CP) is well-suited for uncertainty quantification in time series forecasting due to its distribution-free coverage guarantees.

Overcoming Rank Collapse in Feedback Alignment

arXiv:2606.11123v1 Announce Type: new Abstract: Backpropagation (BP) is widely viewed as biologically implausible, in part because it requires feedback weights to be the transpose of forward weights f

P3D-Bench: Benchmarking MLLMs for Parametric 3D Generation and Structural Reasoning

arXiv:2606.11152v1 Announce Type: new Abstract: Multimodal large language models can write code to produce complex programs as well as use programs to do 3D modeling, which opens up a new avenue for 3

Parallel Causal Associative Fields: Gated Sparse Memory for Long-Context Language Modeling

arXiv:2606.10435v1 Announce Type: cross Abstract: Transformers achieve strong language modeling performance by providing direct token-to-token communication paths, but causal self-attention scales qua

Parametric Knowledge is Not All You Need: Toward Honest Large Language Models via Retrieval of Pretraining Data

arXiv:2601.21218v2 Announce Type: replace Abstract: Large language models (LLMs) are highly capable of answering questions, but they are often unaware of their own knowledge boundary, i.e., knowing wh

PhantomBench: Benchmarking the Non-existential Threat of Language Models

arXiv:2606.11105v1 Announce Type: cross Abstract: Hallucinations, where language models (LMs) generate factually ungrounded responses, pose serious risks, as users tend to blindly rely on them. This i

Piper: A Programmable Distributed Training System

arXiv:2606.11169v1 Announce Type: cross Abstract: Large-scale model training increasingly relies on composing multiple parallelism strategies, such as data, pipeline, and expert parallelism, together