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arXiv:2607.05032v1 Announce Type: new Abstract: Background: Disease severity is a multidimensional construct difficult to capture with rule-based approaches in Electronic Healthcare Records (EHR). Age

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Model Releases

Obey, Diverge, Collapse: Blind Obedience to Incorrect Instructions Drives Code LLMs to Irrecoverable Code Semantic Collapse

DGX agent

arXiv:2607.04537v1 Announce Type: cross Abstract: Code language models are now trusted collaborators in production workflows for debugging, refactoring, and iterative repair, and every benchmark that

model-releasesarxiv-cs-ai

7 Jul 2026

Re:Form -- Reducing Human Annotations in Scalable Formal Software Verification with RL in LLMs: A Preliminary Study on Dafny

model-releasesarxiv-cs-cl

arXiv:2507.16331v4 Announce Type: replace Abstract: Existing informal language-based (e.g., human language) Large Language Models (LLMs) trained with Reinforcement Learning (RL) face a significant cha

Robust Counterfactual Explanations under Model Multiplicity Using Multi-Objective Optimization

arXiv:2501.05795v4 Announce Type: replace-cross Abstract: In recent years, explainability in machine learning has gained importance. In this context, counterfactual explanation (CE), which is an expla

Self-Reference in Large Language Models: The Introspection Threshold for Recursive Self-Improvement

arXiv:2607.04277v1 Announce Type: cross Abstract: The pursuit of self-evolving AI raises a critical question: when is autonomous self-improvement sustainable rather than degenerative? Drawing an analo

SynSFX: Multi-Model Sound Effects Synthesis Dataset for Deepfake Detection and Evaluation

arXiv:2607.04848v1 Announce Type: cross Abstract: While audio deepfake detection has advanced significantly, representative detectors show limited generalization to synthetic sound effects. Existing e

TexTailor: Inference-Time Textual Guidance Tailoring for Multimodal Diffusion Transformers

model-releasesarxiv-cs-cv

arXiv:2601.02211v2 Announce Type: replace Abstract: Recent breakthroughs of transformer-based diffusion models, particularly with Multimodal Diffusion Transformers (MMDiT) driven models like FLUX and

The problem with Anthropic's consciousness paper My last post got more attention than I expected, and the question I keep getting is some ve…

model-releasesgary-marcus--x

The problem with Anthropic's consciousness paper My last post got more attention than I expected, and the question I keep getting is some version of 'okay, so what is actually wrong with the paper?'.

Hardware

How Open Models Are Driving AI Research

Every year, the International Conference on Machine Learning (ICML) reveals where thousands of AI researchers have decided to put their work. This year’s accepted papers reveal a clear direction: open

hardwarenvidia-blog

6 Jul 2026

Must-read research by Anthropic. Here is the simple explanation and why this is a big deal. We suspect LLMs perform 'internal reasoning'. Bu…

Must-read research by Anthropic. Here is the simple explanation and why this is a big deal. We suspect LLMs perform 'internal reasoning'. But little is known or do good methods exist to understand it.

model-releasesdair-ai--x

6 Jul 2026

Industry

Teaching models to forget: Selective unlearning with Amazon Nova

In this post, we introduce Reverse Direct Preference Optimization (rDPO), the novel unlearning technique behind Amazon Nova Customizable Content Moderation Settings (CCMS), and show how it reduces ove

industryaws-ml-blog

6 Jul 2026

ADMC: Attention-based Diffusion Model for Missing Modalities Feature Completion

arXiv:2507.05624v2 Announce Type: replace Abstract: Multimodal emotion and intent recognition is essential for automated human-computer interaction, It aims to analyze users' speech, text, and visual

CoRe: Combined Rewards with Vision-Language Model Feedback for Preference-Aligned Reinforcement Learning

arXiv:2607.01721v1 Announce Type: new Abstract: Reward design remains a central challenge in reinforcement learning (RL). Hand-crafted rewards are often difficult to specify and may lead to suboptimal

safetyarxiv-cs-ro

Epistemic Goggles: A Pretrained Module that Induces an Epistemic Frame via Gradient Editing

arXiv:2607.01690v1 Announce Type: new Abstract: Finetuning a language model on documents that are explicitly annotated as fictional results in a model that still actually believes the documents' core

Exploring Large Language Models for Access Control Policy Synthesis and Summarization

arXiv:2510.20692v2 Announce Type: replace-cross Abstract: Cloud computing is ubiquitous, with a growing number of services being hosted on the cloud every day. Typical cloud compute systems allow admi

Tutorials

G-RRM: Guiding Symbolic Solvers with Recurrent Reasoning Models

arXiv:2607.02491v1 Announce Type: new Abstract: In this work, we focus on SE-RRMs, a symbol-equivariant instantiation of RRMs that exhibits improved extrapolation to larger problem sizes. We propose a

tutorialsarxiv-cs-ai

Generative AI and Federated Learning for Intrusion Detection Systems: A Survey

arXiv:2607.01305v1 Announce Type: cross Abstract: Intrusion Detection Systems (IDSs) are essential for monitoring network traffic and identifying malicious activities in modern cyber-physical, Interne

HarnessX: A Composable, Adaptive, and Evolvable Agent Harness Foundry

arXiv:2606.14249v2 Announce Type: replace Abstract: AI agent performance depends critically on the runtime harness, comprising the prompts, tools, memory, and control flow that mediate how a model obs

OpenAI offers feds a stake, Anthropic gets out of AI model jail and Meta wants to be a neocloud

OpenAI reportedly has floated giving the U.S. government a 5% stake in the company, perhaps the start of a series of such stakes in other AI companies as well. This no doubt has traditional anti-indus

safetysiliconangle

Robust for the Wrong Reasons: The Representational Geometry of LLM Robustness to Science Skepticism

arXiv:2607.01951v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly consulted on contested scientific questions, raising the concern that they will sycophantically retreat

Safety Targeted Embedding Exploit via Refinement

arXiv:2607.01859v1 Announce Type: new Abstract: Safety training for large language models (LLMs) is conducted predominantly in English, leaving uncertain how well safety mechanisms generalize to low-r

Towards Robustness against Typographic Attack with Training-free Concept Localization

model-releasesarxiv-cs-cl

arXiv:2607.02494v1 Announce Type: cross Abstract: Models trained via Contrastive Language-Image Pretraining (CLIP) serve as the foundational vision encoders for most modern Large Vision Language Model

WARP: Weight-Space Analysis for Recovering Training Data Portfolios

model-releasesarxiv-cs-lg

arXiv:2607.01686v1 Announce Type: new Abstract: Foundation models are routinely released to the public, yet the data recipes used to train them -- such as domain mixture weights that determine how dif

World Wide Models: Literary Tools for Cultural AI

arXiv:2607.02369v1 Announce Type: cross Abstract: LLMs stage a new form of cultural encounter that is massive, automated, and monolingual. Literary disciplines have always negotiated cultural struggle

A Geometric Perspective on Composable Emotion Steering in Text-to-Speech Models

arXiv:2607.00946v1 Announce Type: cross Abstract: While prior work has explored emotion control in hybrid text-to-speech systems, the geometric properties of these modules, and their implications for

researcharxiv-cs-lg

Adversarial Pragmatics for AI Safety Evaluation: A Benchmark for Instruction Conflict, Embedded Commands, and Policy Ambiguity

arXiv:2607.01153v1 Announce Type: cross Abstract: Safety evaluations for language models increasingly depend on judgments about ambiguous natural-language behaviour: whether a model has followed an in

BaseRT: Best-in-Class LLM Inference on Apple Silicon via Native Metal

arXiv:2607.00501v1 Announce Type: cross Abstract: We present BaseRT, a native Metal inference runtime for large language models (LLMs) on Apple Silicon, and report the highest inference throughput on

BrainFIBRE: A Foundation Model via Information Decomposition for Brain Microstructure

arXiv:2607.00573v1 Announce Type: new Abstract: Diffusion MRI probes brain microstructure with particular sensitivity to early cerebrovascular and neurodegenerative changes. Neurite Orientation Disper

safetyarxiv-cs-cv

Bridgewater just published numbers that should make every frontier lab nervous. The world's largest hedge fund tested Gemini, Claude, and GP…

model-releasesclem-delangue--x

Bridgewater just published numbers that should make every frontier lab nervous. The world's largest hedge fund tested Gemini, Claude, and GPT on six document filtering tasks its investors do every day

FastBridge: Closing the Model-Based Realization Gap in Safety Filters on 3D Gaussian Splatting for Fast Quadrotor Flight

arXiv:2607.01200v1 Announce Type: new Abstract: Fast quadrotor flight requires safe obstacle avoidance under tight onboard compute limits. While 3D Gaussian Splatting (3DGS) provides a continuous, geo

safetyarxiv-cs-ro

Applications

FurnitureVLA: Learning Long-Horizon Bimanual Furniture Assembly with Vision-Language-Action Model

arXiv:2607.01212v1 Announce Type: cross Abstract: Current work on robot furniture assembly mostly focuses on toy-scale settings or single-arm manipulation. We introduce FurnitureVLA, the first systema

applicationsarxiv-cs-ai

FusionFactory: Fusing LLM Capabilities with Multi-LLM Log Data

model-releasesarxiv-cs-lg

arXiv:2507.10540v3 Announce Type: replace Abstract: The rapid advancement of large language models (LLMs) has created a diverse landscape of models, each excelling at different tasks. This diversity d

Is One Layer Enough? Training A Single Transformer Layer Can Match Full-Parameter RL Training

model-releasesarxiv-cs-cl

arXiv:2607.01232v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a central component of post-training large language models (LLMs), yet little is understood about how RL adapta

Agents

Neural Surface and Reflectance Modelling from 3D Radar Data

arXiv:2603.25623v2 Announce Type: replace Abstract: Robust scene representation is essential for autonomous systems to safely operate in challenging low-visibility environments. In these conditions, r

agentsarxiv-cs-ro

OpenReward: Learning to Reward Long-form Agentic Tasks via Reinforcement Learning

arXiv:2510.24636v3 Announce Type: replace Abstract: Reward models (RMs) have become essential for aligning large language models (LLMs), serving as scalable proxies for human evaluation in both traini

safetyarxiv-cs-cl

PAPA: Online Personalized Active Preference Alignment

arXiv:2607.00486v1 Announce Type: cross Abstract: Diffusion models are highly effective at modeling complex data distributions, including images and text. However, in applications like personalized re

Local Ai

Personalized Object Identification and Localization via In-Context Inference with Vision-Language Models

arXiv:2607.00357v1 Announce Type: new Abstract: Personalized object localization (POL) localizes an object instance in a query image based on a few reference images with bounding-box annotations and a

local-aiarxiv-cs-cv

Spatio-Temporal Gaussian Process for Building Terrain-Incorporating Wind Power Curves

arXiv:2607.00051v1 Announce Type: cross Abstract: Accurate modeling of wind turbine power curves is crucial for optimal wind farm operation. Nearly all existing power curve models focus on temporal va

safetyarxiv-cs-lg

SpiralFovea: Input-Adaptive Foveated Tokenization as a Third Lever of Resource-Adaptive Inference

model-releasesarxiv-cs-cv

arXiv:2607.00780v1 Announce Type: new Abstract: Most adaptive-inference techniques for foundation models change what the model does - early exit, MoE routing, KV-cache compression, dynamic attention s

Local Ai

StateFlow: Dual-State Recurrent Modeling for Long-Horizon Time Series Forecasting

arXiv:2607.00197v1 Announce Type: new Abstract: Long-horizon multivariate time series forecasting (LTSF) remains challenging due to non-stationarity, regime shifts, and error accumulation. The Variabi

local-aiarxiv-cs-lg

Applications

The MMM Data Model -- A Normative Specification for Knowledge Interoperability in a Decentralisable Knowledge Commons

arXiv:2607.00032v1 Announce Type: new Abstract: Many information systems are built around documents: self-contained units optimised for print production and linear reading. While effective for large-s

applicationsarxiv-cs-ai

CharDiff-LP: A Diffusion Model with Character-Level Guidance for License Plate Image Restoration

arXiv:2510.17330v3 Announce Type: replace-cross Abstract: License plate image restoration is important not only as a preprocessing step for license plate recognition but also for enhancing evidential

Agents

DSIP: A Dynamic Coordination Planner for Signal-Free Intersections using Diffusion-Model-Based Multi-Agent Motion Planning

arXiv:2606.30694v1 Announce Type: cross Abstract: Traffic signal control at urban intersections inherently introduces stop-and-go behavior, resulting in increased delays and reduced traffic efficiency

agentsarxiv-cs-ai

Localized Conformal Prediction for Image Classification with Vision-Language Models

arXiv:2606.31577v1 Announce Type: new Abstract: Conformal predictions have attracted significant attention in the field of uncertainty quantification, mainly because of their strong marginal coverage

researcharxiv-cs-cv

Minimizing Quantized Semantic Age of Information (QSAoI) in Foundation Model-Based Semantic Communications

arXiv:2606.31303v1 Announce Type: cross Abstract: The emerging techniques of semantic communications and edge computing in 6G networks necessitate a paradigm shift toward co-designed semantic-aware an

Optimal Self-Consistency for Efficient Reasoning with Large Language Models

arXiv:2511.12309v2 Announce Type: replace-cross Abstract: Self-consistency (SC) is a widely used test-time inference technique for improving performance in chain-of-thought reasoning. It consists of g

Applications

RCL-Mamba: A Dual-domain State Space Model for Measurement-oriented Image Restoration in Rotational Sparse-View Scanning Computed Laminography

arXiv:2606.31353v1 Announce Type: new Abstract: Rotational Scanning Computed Laminography (RCL) is widely utilized for the Non-Destructive Testing(NDT) of large planar components. However, to facilita

applicationsarxiv-cs-cv

Structure-Regularized Interpretable TCR-Epitope Prediction

model-releasesarxiv-cs-lg

arXiv:2606.30902v1 Announce Type: cross Abstract: T cell receptor (TCR)-epitope binding prediction is essential for understanding adaptive immunity and developing immunotherapies. Existing sequence- a