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A Judge-Aware Ranking Framework for Evaluating Large Language Models without Ground Truth

arXiv:2601.21817v3 Announce Type: replace-cross Abstract: Evaluating large language models (LLMs) on open-ended tasks without ground-truth labels is increasingly done via the LLM-as-a-judge paradigm.

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Model Releases

A Lightweight Multi-Agent Framework for Automated Concrete Barrier Design

DGX agent

arXiv:2606.12040v1 Announce Type: new Abstract: The design of reinforced concrete highway barriers is a safety-critical process that requires strict compliance with regulatory provisions such as the A

model-releasesarxiv-cs-ai

11 Jun 2026

Applications

A Modular Dual-Camera Pipeline for Micro-Inspection Using Aerial Robots

arXiv:2606.11419v1 Announce Type: new Abstract: Most existing drone-based inspection systems require the drone to fly dangerously close to the target or follow complex flight paths to capture small de

applicationsarxiv-cs-ro

Local Ai

A Multi-Modal Sensor Fusion Instrument for Measuring Regional Human Mobility: The Distributed Human Data Engine (DHDE)

arXiv:2603.21639v2 Announce Type: replace-cross Abstract: Accurately estimating human mobility in peripheral regional economies presents a fundamental measurement challenge: physical ground-truth sens

local-aiarxiv-cs-lg

A Physics-Inspired Optimizer: Velocity Regularized Adam

arXiv:2505.13196v3 Announce Type: replace-cross Abstract: We introduce Velocity-Regularized Adam (VRAdam), a physics-inspired optimizer for training deep neural networks that draws on ideas from quart

A prior-free blind detection of information leakage from model predictions

arXiv:2606.11267v1 Announce Type: new Abstract: Data leakage -- contamination of a model with information unavailable at baseline -- is the dominant reproducibility failure in machine-learning-based s

A PubMed-Scale Dataset of Structured Biomedical Abstracts

arXiv:2606.11361v1 Announce Type: cross Abstract: Structured abstracts are important for biomedical literature processing, by facilitating information retrieval, text mining, and knowledge synthesis.

A Resource for Enthymeme Detection in Controversial Political Discourse

arXiv:2606.12186v1 Announce Type: new Abstract: Enthymemes, arguments with unstated premises or conclusions, are pervasive in persuasive discourse, yet their annotation remains notoriously subjective.

researcharxiv-cs-cl

A Riemannian Approach to Low-Rank Optimal Transport

arXiv:2606.12120v1 Announce Type: new Abstract: Low-rank optimal transport (OT) mitigates the quadratic scaling of classical solvers, yet existing approaches rely heavily on first-order mirror-descent

Hardware

A Scalable PyTorch Abstraction for Multi-GPU Gaussian Splatting

arXiv:2606.11390v1 Announce Type: new Abstract: Gaussian splatting methods have become increasingly popular for neural reconstruction of the real world. However, they are often limited in scale and re

hardwarearxiv-cs-cv

A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models

arXiv:2509.11575v3 Announce Type: replace Abstract: Time series reasoning treats time as a first-class axis and incorporates intermediate evidence directly into the answer. This survey defines the pro

Applications

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data

arXiv:2601.17717v3 Announce Type: replace Abstract: Large Language Models (LLMs) have emerged as powerful tools for generating data across various modalities. By transforming data from a scarce resour

applicationsarxiv-cs-ai

A theory of learning data statistics in diffusion models, from easy to hard

arXiv:2603.12901v2 Announce Type: replace-cross Abstract: While diffusion models have emerged as a powerful class of generative models, their learning dynamics remain poorly understood. We address thi

safetyarxiv-cs-lg

A true honor to be listed in this sentence with @demishassabis. ❤️🙏

Gary Marcus expresses appreciation for being mentioned alongside Demis Hassabis, the co-founder of DeepMind, in what appears to be a recognition or honor-related context. The post reflects Marcus's re

safetygary-marcus--x

Local Ai

A Turbo-Inference Strategy for Object Detection and Instance Segmentation

arXiv:2606.12371v1 Announce Type: new Abstract: Object detection and instance segmentation tasks are closely related. Existing top-down instance segmentation methods usually follow a detect-then-segme

local-aiarxiv-cs-cv

A2SG:Adaptive and Asymmetric Surrogate Gradients for Training Deep Spiking Neural Networks

arXiv:2606.11236v1 Announce Type: cross Abstract: Training deep spiking neural networks (SNNs) remains challenging due to sharp loss landscapes and temporal inconsistency caused by surrogate gradients

researcharxiv-cs-cv

Tutorials

Accurate and Resource-Efficient Federated Continual Learning

arXiv:2606.11480v1 Announce Type: new Abstract: Federated continual learning (FCL) must learn from distributed task streams under limited resources, such as communication, computation, memory, and lab

tutorialsarxiv-cs-lg

Adapting Prithvi-EO for Fallow Detection for Food-Water Nexus: ViT-Adapter Necks and Parameter-Efficient Backbone tuning of Geospatial Foundation Model

arXiv:2606.12218v1 Announce Type: cross Abstract: Understanding spatial distribution of fallow land is important for optimizing the food-water (FW) nexus, given fallowing's role in crop rotation and w

Adapting Vision-Language Models from Iconic to Inclusive for Multi-Label Recognition Without Labels

arXiv:2606.11626v1 Announce Type: new Abstract: Understanding multi-label images remains a challenging task in computer vision. With the rapid progress of vision-language multimodal learning, vision-l

safetyarxiv-cs-cv

Adaptive Multi-Resolution Procedural Knowledge Compression for Large Language Models

arXiv:2606.12203v1 Announce Type: new Abstract: Large language models (LLMs) are widely used to tackle complex tasks with autonomous workflows. Recently, reusable natural language skills have emerged

Adjoint Method versus Physics-Informed Neural Networks in PDE-Constrained Inverse Problems

arXiv:2606.12337v1 Announce Type: cross Abstract: Inverse problems governed by partial differential equations (PDEs) are central to computational mechanics and are commonly solved by adjoint-based opt

Adv-TGD: Adversarial Text-Guided Diffusion for Face Recognition Impersonation Attacks

arXiv:2606.11615v1 Announce Type: new Abstract: The widespread adoption of face recognition (FR) technologies raises serious privacy concerns, as facial data can be exploited without consent. To addre

safetyarxiv-cs-cv

Adversarial Attacks on Learned Policies for Surgical Robotic Tasks

arXiv:2606.11535v1 Announce Type: new Abstract: Learning-based policies are being considered to augment the dexterity of human surgeons in robot-assisted surgery. Can the end-to-end mapping from visua

safetyarxiv-cs-ro

AerialClaw: An Open-Source Framework for LLM-Driven Autonomous Aerial Agents

arXiv:2606.12142v1 Announce Type: cross Abstract: Unmanned aerial vehicles (UAVs) are increasingly used in inspection, search and rescue, environmental monitoring, and emergency response. However, mos

safetyarxiv-cs-cv

Afrispeech Semantics: Evaluating Audio Semantic Reasoning in Spoken Language Models Across Domains and Accents

arXiv:2606.11219v1 Announce Type: cross Abstract: Audio language models (ALMs) are increasingly used for speech-based understanding, yet their ability to perform semantic reasoning beyond transcriptio

researcharxiv-cs-ai

Tutorials

AGE-MIL: Anchor-Guided Evidence Learning for Patient-Level Prediction

arXiv:2606.12126v1 Announce Type: new Abstract: Existing computational pathology methods predominantly operate within whole-slide image (WSI)-level multiple instance learning (MIL) paradigms, while pa

tutorialsarxiv-cs-cv

Agent Skill Evaluation and Evolution: Frameworks and Benchmarks

arXiv:2606.11435v1 Announce Type: new Abstract: The growth of agent skills has transformed how agentic systems are built, evaluated, and deployed. As skill libraries continue to scale, rigorous evalua

Agents

Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application

arXiv:2606.12191v1 Announce Type: cross Abstract: Environments serve as interactive systems for large language model (LLM) based agents across diverse scenarios and play a crucial role in driving the

agentsarxiv-cs-ai

Agents

Agents All the Way Down; A Methodology for Building Custom AI Agents from Substrate to Production

arXiv:2606.11869v1 Announce Type: cross Abstract: Custom AI agents areagents that live inside their own application, talk to their own data and tools, enforce their own security boundaries, and carry

agentsarxiv-cs-ai

Agreement in Representation Space for Open-Ended Self-Consistency

arXiv:2606.12003v1 Announce Type: new Abstract: Self-consistency improves LLM reasoning by sampling multiple outputs and selecting the most consistent answer, but existing formulations largely rely on

researcharxiv-cs-cl

AI Coding Agents Can Reproduce Social Science Findings

arXiv:2606.11447v1 Announce Type: new Abstract: Recent anecdotal evidence suggests that AI coding agents can reproduce published findings when provided with original data and code; yet systematic eval

AI Coding Agents in Social Science: Methodologically Diverse, Empirically Consistent, Interpretively Vulnerable

arXiv:2606.11456v1 Announce Type: cross Abstract: The deployment of LLM-based agents in scientific analysis raises opposing concerns: that agents may reduce methodological diversity, or that they may

AI Researchers Must Help Lead Arms Control to Mitigate Military AI Risks

arXiv:2606.11533v1 Announce Type: cross Abstract: The advancement of AI capabilities compels researchers and the public to be more aware of its potential worldwide impact. A pressing near-term concern

Hardware

AI4Land: Scalable Deep Learning for Global High-Resolution Land Use Reconstruction

arXiv:2606.11793v1 Announce Type: cross Abstract: Uncertainty in the terrestrial carbon cycle remains a major constraint in climate projections, partly driven by the uncertainties affecting the land s

hardwarearxiv-cs-ai

AI4SLT: Empirical Processes in Lean 4 for Formal Statistical Learning Theory

arXiv:2602.02285v2 Announce Type: replace-cross Abstract: We present the first comprehensive Lean 4 formalization of statistical learning theory (SLT) grounded in empirical process theory. Our en-to-e

researcharxiv-cs-cl

Agents

[AINews] Open Models, Model Labs vs Agent Labs, and What's Untrainable — Sarah Guo

This episode discusses the growing landscape of open-source AI models, contrasts the approaches and philosophies of Model Labs versus Agent Labs in AI development, and explores fundamental limitations

agentslatent-space

ALIGNBEAM : Inference-Time Alignment Transfer via Cross-Vocabulary Logit Mixing

arXiv:2606.12342v1 Announce Type: cross Abstract: Domain fine-tuning degrades the safety of large language models: fine-tuned specialists readily comply with harmful prompts framed in domain language.

Local Ai

Ambient Diffusion Policy: Imitation Learning from Suboptimal Data in Robotics

arXiv:2606.12365v1 Announce Type: cross Abstract: We propose Ambient Diffusion Policy, a simple and principled method for imitation learning from suboptimal data in robotics. High-quality, task-specif

local-aiarxiv-cs-ai

An Electric Potential-Augmented Benchmark Dataset for Physics-Guided Image Reconstruction of Electrical Capacitance Tomography

model-releasesarxiv-cs-cv

arXiv:2606.12226v1 Announce Type: new Abstract: While deep learning has significantly advanced image reconstruction of Electrical Capacitance Tomography (ECT), most data-driven methods map directly be

An Ethical eValuation Agent (EeVA): Results of a Proof-of-Concept Test on a Prototype Agentic-like Workflow to Assist Ethical Deliberations

arXiv:2606.11218v1 Announce Type: cross Abstract: Ethical deliberation is often misunderstood as a search for single right or wrong answers, creating difficulties for non-ethically trained personnel w

An Ontology-Guided Multi-Anchor Graph Retrieval Framework for Traffic Legal Liability Determination

arXiv:2606.11910v1 Announce Type: new Abstract: Traffic law liability determination is critical for assigning legal penalties, requiring the simultaneous identification of interdependent statutory pro

An XAI View on Explainable ASP: Methods, Systems, and Perspectives

arXiv:2601.14764v2 Announce Type: replace Abstract: Answer Set Programming (ASP) is a popular declarative reasoning and problem solving approach in symbolic AI. Its rule-based formalism makes it inher

researcharxiv-cs-ai

Industry

Analysis: Conservative and Reform UK MPs have increased their volume of posts on X since Elon Musk's takeover, while center-left politicians have reduced theirs (Financial Times)

Financial Times: Analysis: Conservative and Reform UK MPs have increased their volume of posts on X since Elon Musk's takeover, while center-left politicians have reduced theirs — Majority of Labour a

industrytechmeme

Analytic Bijections for Smooth and Interpretable Normalizing Flows

arXiv:2601.10774v2 Announce Type: replace Abstract: A key challenge in normalizing flows is finding expressive invertible scalar bijections. Existing approaches face trade-offs: affine transformations

Anatomically Conditioned Recurrent Refinement for Topology-Aware Circle of Willis Segmentation

arXiv:2606.12319v1 Announce Type: new Abstract: Segmenting the Circle of Willis (CoW) from Magnetic Resonance Angiography (MRA) is challenging due to complex topology and thin vascular structures that

researcharxiv-cs-cv

Tutorials

Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal

arXiv:2606.12360v1 Announce Type: new Abstract: Language-model post-training is the main stage at which model behavior is shaped, yet it still largely involves optimization of scalar rewards that summ

tutorialsarxiv-cs-lg

AnchorEdit: Maintaining Temporal Consistency in Multi-turn Image Editing via Causal Memory

arXiv:2606.11751v1 Announce Type: cross Abstract: Multi-turn image editing is essential for iterative design, yet current models often struggle with identity drift and error accumulation over successi

and now the possible of drastic price cuts, a further sign of OpenAI’s desperation, as foreseen by me 2.5 years ago:

and now the possible of drastic price cuts, a further sign of OpenAI’s desperation, as foreseen by me 2.5 years ago: Called the LLM price wars – which are about to heat up — over two years ago. See es

safetygary-marcus--x