Search: “models”

DLR: Zero-Inference-Cost Latent Residuals for Low-Rank Pre-Training

arXiv:2606.28932v1 Announce Type: cross Abstract: Large language models have driven recent progress in language and multimodal AI, yet pre-training them at scale is prohibitively expensive. Low-rank p

DRIFT: Difficulty Routing Self-DIstillation with Rhythm-Gated Exploration and Success BuFfer Training

DGX agent

arXiv:2606.30345v1 Announce Type: cross Abstract: Enabling large language models to achieve stable self-improvement without external expert supervision remains a central challenge in complex reasoning

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30 Jun 2026

Dynamic Parsing and Updating Natural Language Specification using VLMs for Robust Vision-Language Tracking

arXiv:2606.29357v1 Announce Type: cross Abstract: Vision-language tracking guided by natural language specifications leverages high-level semantic cues of target objects to substantially boost trackin

Dynamo: Dynamic Skill-Tool Evolution for Vision-Language Agents

arXiv:2606.30185v1 Announce Type: new Abstract: Improving vision-language models (VLMs) on visual reasoning typically requires retraining or hand-designed prompts and tools. We present Dynamo, a train

EVLA: An Electro-Aware Multimodal Assistant for Physically-Grounded Driving Reasoning and Control

arXiv:2606.28938v1 Announce Type: new Abstract: Modern vision-language models (VLMs) for driving assistants typically treat vehicle dynamics as a black box, resulting in decisions that lack awareness

Experience Augmented Policy Optimization for LLM Reasoning

arXiv:2606.30420v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is a powerful paradigm for improving the reasoning capabilities of large language models (LLMs). H

Research

Few-Step Boltzmann Generators via Scalable Likelihood Flow Maps

arXiv:2606.29110v1 Announce Type: new Abstract: Recent progress in flow-based generative modeling has led to models that output high-quality samples while using only a small number of function evaluat

researcharxiv-cs-lg

Generalization Analysis of Transformers in Distribution Regression

arXiv:2606.29256v1 Announce Type: cross Abstract: In recent years, models based on the Transformer architecture have seen widespread applications and have become one of the core tools in the field of

Heterogeneous Tactile Transformer

model-releasesarxiv-cs-ro

arXiv:2606.29948v1 Announce Type: new Abstract: Tactile sensors are inherently heterogeneous: a model trained on one sensor cannot be directly used on another, which limits learning contact-rich manip

How Far Can You Get Without a GPU? A Systematic Benchmark of Lightweight Hallucination Detection Across Question Answering, Dialogue, and Summarisation

arXiv:2606.29809v1 Announce Type: cross Abstract: Hallucination detection has become a pressing requirement for trustworthy AI deployment at scale. The most accurate detection methods depend on GPU-in

How much of an LLM-generated clinical corpus is actually new? A production-scale measurement of content redundancy for provenance classification

arXiv:2606.29605v1 Announce Type: new Abstract: Clinical machine learning increasingly relies on training corpora generated by large language models (LLMs) rather than annotated by clinicians, and suc

I-BBS: Coordinate-Free Inference of Latent Sub-Manifolds Using Random Distance Matrix Theory

arXiv:2606.29675v1 Announce Type: new Abstract: Bogomolny, Bohigas and Schmit (BBS) found that the spectrum of the pairwise distance matrix on N points sampled from a smooth d-dimensional manifold enc

Intermediate Text Representation Guided Text-to-Image Generation for Enhancing One-and-Only Alignment

arXiv:2606.30262v1 Announce Type: new Abstract: Text-to-image (T2I) diffusion models often fail to faithfully render explicit textual descriptions, instead defaulting to strongly learned visual priors

Introducing GeneBench-Pro

GeneBench-Pro is a comprehensive benchmarking tool or dataset introduced by OpenAI designed to evaluate AI model performance on genomic and gene-related tasks. It likely provides standardized metrics

model-releasesopenai

LoGSAM: Parameter-Efficient Cross-Modal Grounding for MRI Segmentation

arXiv:2603.17576v3 Announce Type: replace Abstract: Precise localization and delineation of brain tumors using magnetic resonance imaging (MRI) are essential for planning therapy and guiding surgical

LUMEN: Cost-Transparent Multi-Agent Pipeline for Automated Systematic Review and Meta-Analysis

arXiv:2606.28362v1 Announce Type: cross Abstract: Systematic reviews and meta-analyses (SR/MA) remain the gold standard for evidence synthesis, yet completing one typically requires 67 weeks and subst

Multimodal Graph RAG for Long-range Visually Rich Document Understanding

arXiv:2606.28780v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are widely applied to visual document understanding. However, comprehending long documents remains an issue b

Multimodal Mathematical Reasoning with Diverse Solving Perspective

arXiv:2507.02804v2 Announce Type: replace Abstract: Recent progress in large-scale reinforcement learning (RL) has notably enhanced the reasoning capabilities of large language models (LLMs), especial

Nano Banana 2 Lite

model-releasessimon-willison

Nano Banana 2 Lite Also known as Gemini 3.1 Flash Lite Image (gemini-3.1-flash-lite-image in their API), this is the 'fastest and cheapest Gemini image model, engineered for velocity and scale'. I use

Not-quite-human tastes: the stylized omnivorousness of LLM survey surrogates

arXiv:2606.30085v1 Announce Type: new Abstract: Large-language models have proven to be remarkable if inconsistent parrots of public attitudes and opinions. The extent to which LLMs are able to produc

OP3DSG: Open-Vocabulary Part-Aware 3D Scene Graph Generation for Real-World Environments

arXiv:2606.29786v1 Announce Type: new Abstract: 3D scene graphs (3DSGs) provide a compact and structured abstraction of 3D environments. Although advances in foundation models have enabled open-vocabu

Research

Perspectives on Latent Factor Indeterminacy and its Implications for Data Representation

arXiv:2606.28854v1 Announce Type: cross Abstract: The common factor analytic model is related to Helmholtz and Boltzmann machines, can be conceived as a linear autoencoder, or can be thought of as a s

researcharxiv-cs-ai

REAR: Test-time Preference Realignment through Reward Decomposition

arXiv:2606.30339v1 Announce Type: new Abstract: Aligning large language models (LLMs) with diverse user preferences is a critical yet challenging task. While post-training methods can adapt models to

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REPAIR-Bench: A Benchmark for Robot Error Perception And Interaction Recovery

model-releasesarxiv-cs-ro

arXiv:2606.29937v1 Announce Type: new Abstract: Understanding how users perceive and respond to robot failures is essential for building robust and trustworthy robot systems. Prior work, however, (i)

Reported Confidence in LLMs Tracks Commitment More Than Correctness

arXiv:2606.29490v1 Announce Type: cross Abstract: Confidence is an estimate of the probability that a chosen answer is correct. Verbal confidence reports are widely used as uncertainty measures in lar

Reward-Free Code Alignment from Pretrained or Fine-Tuned LLM: Unpacking the Trade-offs for Code Generation

arXiv:2606.28998v1 Announce Type: cross Abstract: Large Language Model (LLM) alignment trains an LLM using preference data to produce outputs that better meet established quality standards. While LLM

SafePyramid: A Hierarchical Benchmark for In-context Policy Guardrailing

arXiv:2606.29887v1 Announce Type: new Abstract: In real-world applications, guardrails are often expected to identify unsafe user-model interactions according to application-specific safety policies,

Semantic-Driven Scale and Spatial Selection for Efficient Cross-Modal Alignment in Referring Remote Sensing Image Segmentation

arXiv:2606.30244v1 Announce Type: new Abstract: Referring Remote Sensing Image Segmentation (RRSIS) seeks to localize and segment the target object or region specified by a natural language expression

Symbolic Mechanistic Data Attribution: Tracing Training Influence to Learned Behavioral Policies

arXiv:2606.29171v1 Announce Type: cross Abstract: While existing data attribution methods can identify which training examples build specific mechanistic circuits, they cannot explain how training dat

TF-MoE: Time-Frequency Mixture-of-Experts for Efficient Speech Separation

arXiv:2606.29575v1 Announce Type: cross Abstract: Recent advances in speech separation (SS) have led to compact front-end models with small parameter sizes, yet their high computational cost remains a

Research

The Fundamental Limits of Valid Transport Map Estimation

arXiv:2606.30574v1 Announce Type: new Abstract: Many modern generative modeling methods, including diffusion models, normalizing flows, and flow matching, estimate transport maps or plans between dist

researcharxiv-cs-lg

Towards Physical Intuitions for Alignment Dynamics: A Case Study With Randomness Crystallization

arXiv:2606.29933v1 Announce Type: new Abstract: The alignment of language models is typically studied through the lens of capability benchmarks, but the dynamics of how models change during post-train

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TriageRA-CCF: Source-Side Clinical Confidence and Coverage Signals for Adaptive Rank Budgeting in Medical LLMs

arXiv:2606.29375v1 Announce Type: new Abstract: Medical large language models are commonly adapted with a fixed low-rank budget, even though medical questions differ substantially in confidence, clini

UniGP: Taming Diffusion Transformer for Prior-Preserved Unified Generation and Perception

arXiv:2606.30332v1 Announce Type: new Abstract: Recent advances in diffusion models have shown impressive performance in controllable image generation and dense prediction tasks. However, existing app

safetyarxiv-cs-cv

Why Trust Your Agent? Empirical Security Gains from TRiSM-Guided Agentic Workflows in Healthcare

arXiv:2606.28666v1 Announce Type: cross Abstract: Agent-based AI has enabled the automation of tasks by exposing application tools and resources to large language models (LLMs). However, to improve sc

You Only Touch Once: 6-DoF Object Pose Estimation from Single Tactile Contact

model-releasesarxiv-cs-ro

arXiv:2606.28899v1 Announce Type: new Abstract: Accurate 6-DoF object pose estimation is fundamental to robotic manipulation, yet vision-based methods often fail under occlusion, poor lighting, and re

A Comparison of Fusion Techniques for Multi-Modal Human Activity Recognition on the HARMES Dataset

arXiv:2606.27886v1 Announce Type: new Abstract: Recent advances in Human Activity Recognition (HAR) from wearable sensors have shown that multi-modal deep learning models consistently outperform their

Accelerating Attention with Basis Decomposition

arXiv:2510.01718v2 Announce Type: replace Abstract: Attention is a core operation in large language models (LLMs). We present BD Attention (BDA), a lossless algorithmic reformulation of attention. BDA

Alibaba allegedly ran 28.8 million fraudulent API exchanges across 25,000 fake accounts to steal Claude's intelligence. If confirmed, it's t…

model-releasesemad-mostaque--x

Alibaba allegedly ran 28.8 million fraudulent API exchanges across 25,000 fake accounts to steal Claude's intelligence. If confirmed, it's the largest AI model theft ever attempted. The same week, the

Applicability of memorization indicators for early spotting of overfitting while recalibrating sEMG-decoders on low sample sizes

arXiv:2606.27855v1 Announce Type: cross Abstract: Deep learning models for surface electromyography (sEMG) can benefit substantially from subject-specific (re-)calibration, since no sufficiently large

Claude in Microsoft Foundry is now generally available, hosted on Azure. Azure customers get Claude Opus 4.8 and Claude Haiku 4.5, with Azur…

model-releasesboris-cherny--x

Claude models are now generally available through Microsoft Foundry on Azure infrastructure, providing Azure customers access to Claude Opus 4.8 and Claude Haiku 4.5. This integration allows enterpris

Cloud CISO Perspectives: How Google Cloud Security uses AI internally

model-releasesgoogle-cloud-ai

Welcome to the second Cloud CISO Perspectives for June 2026. Today, we’re discussing how we use AI to chart a path to autonomous software development lifecycle security.As with all Cloud CISO Perspect

Contagion Networks: Evaluator Preference Propagation in Multi-Agent LLM Systems

arXiv:2606.20493v2 Announce Type: replace-cross Abstract: When large language models serve as evaluators in multi-agent systems, their strategy preferences -- whether induced by explicit prompts or by

Deployment-Side Adaptiveness in Multi-Horizon Volatility Forecasting

arXiv:2606.27688v1 Announce Type: cross Abstract: In financial forecasting, predictive performance depends not only on which model is trained, but also on how the trained model is deployed. We study t

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Estimation--Prediction Tradeoff in Causal Probabilistic Temporal Graphs

arXiv:2606.28225v1 Announce Type: new Abstract: Temporal link prediction is usually evaluated by predictive performance on unseen edges, but in probabilistic temporal graphs this criterion can conflat

EXPLORE-Bench: Egocentric Scene Prediction with Long-Horizon Reasoning

arXiv:2603.09731v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) are increasingly considered as a foundation for embodied agents, yet it remains unclear whether they

Formalizing Latent Thoughts: Four Axioms of Thought Representation in LLMs

arXiv:2606.27378v1 Announce Type: new Abstract: We introduce an axiomatic evaluation framework for latent thought representations in LLMs, comprising metrics that are independent of downstream benchma

From Detection to Action: Using LLM Agents for Fault-Tolerant Control

arXiv:2606.28011v1 Announce Type: cross Abstract: We propose an agentic Large Language Model (LLM) framework for active Fault-Tolerant Control (FTC) that transforms fault detection outputs into constr