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Annealed Entropic Allocation for Ranking and Selection

model-releasesarxiv-cs-lg

arXiv:2606.11347v1 Announce Type: cross Abstract: We propose Annealed Entropic Allocation, an annealed weighted soft-min framework for sequential budget allocation in ranking and selection. The centra

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Anthropic Walks Back Policy That Could Have ‘Sabotaged’ AI Researchers Using Claude

DGX agent

Anthropic Walks Back Policy That Could Have ‘Sabotaged’ AI Researchers Using Claude Big scoop for Maxwell Zeff at Wired: “We’re changing Fable 5’s safeguards for frontier LLM development to make them

model-releasessimon-willison

11 Jun 2026

Industry

Anthropic’s Dario Amodei wants governments to have the power to block ‘dangerous’ AI systems

Anthropic PBC Chief Executive Dario Amodei is calling on the U.S. government to block the deployment of dangerous artificial intelligence models in the same way as it prevents unsafe airplanes from ta

industrysiliconangle

APEX: A Network-Native Time-Series Foundation Model for Forecasting and Anomaly Detection for Wireless Edge Operations

model-releasesarxiv-cs-lg

arXiv:2606.11553v1 Announce Type: new Abstract: Generic time-series foundation models transfer poorly to wireless network telemetry whose signals are bursty, zero-inflated, and coupled across protocol

APEX: Automated Prompt Engineering eXpert with Dynamic Data Selection

arXiv:2606.11459v1 Announce Type: cross Abstract: Large Language Models are highly sensitive to prompt formulation, necessitating automatic prompt optimization to unlock their full potential. While ev

Applications

Applied Materials opens a $500M chip equipment manufacturing campus in Singapore, making the city-state home to ~50% of its production capacity alongside the US (Cheng Ting-Fang/Nikkei Asia)

Cheng Ting-Fang / Nikkei Asia: Applied Materials opens a 500M chip equipment manufacturing campus in Singapore, making the city-state home to ~50% of its production capacity alongside the US — SINGAPO

applicationstechmeme

APPO: Agentic Procedural Policy Optimization

arXiv:2606.12384v1 Announce Type: cross Abstract: Recent advances in agentic Reinforcement Learning (RL) have substantially improved the multi-turn tool-use capabilities of large language model agents

APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies

arXiv:2606.12366v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models that couple pretrained Vision-Language Models (VLMs) with continuous action experts have achieved strong manipulatio

safetyarxiv-cs-ro

Architecture-Aware Reinforcement Learning Makes Sliding-Window Attention Competitive in Math Reasoning

arXiv:2606.11634v1 Announce Type: new Abstract: The rapid progress of reasoning and agentic large language models (LLMs) has increased the demand for long-context inference, but self-attention (SA) sc

Are LLMs Bad at Moral Reasoning?

arXiv:2606.11635v1 Announce Type: cross Abstract: For highly capable AI systems to operate safely in dynamic, open-ended environments, they must be able to identify, understand, and respond to moral r

researcharxiv-cs-ai

ARGUS: Stacked Multi-View Identity Mosaic Injection for Subject-Preserving Video Generation

arXiv:2606.11670v1 Announce Type: cross Abstract: Subject-preserving video generation is not solved by frontal-face similarity alone: a generated person must remain recognizable across motion, large v

Artificial Intelligence in Ship Finance: Applications, Opportunities, and a Case Study in AI-Augmented Loan Origination

arXiv:2606.11238v1 Announce Type: cross Abstract: Ship finance is a data-intensive and document-heavy segment of asset-based lending, requiring the integration of financial, technical, contractual, an

As featured today by @FT’s Alphaville: “An entire industry is being propped up by math that is insane.” Available only at Marcus on AI, a “f…

Gary Marcus critiques fundamental mathematical or computational problems underlying an entire industry, suggesting widespread reliance on flawed or unsound methodologies. The commentary appears on Mar

safetygary-marcus--x

AsFT: Anchoring Safety During LLM Fine-Tuning Within Narrow Safety Basin

model-releasesarxiv-cs-lg

arXiv:2506.08473v4 Announce Type: replace Abstract: Fine-tuning large language models (LLMs) improves performance but introduces critical safety vulnerabilities: even minimal harmful data can severely

ATLAS: Active Theory Learning for Automated Science

arXiv:2606.12386v1 Announce Type: cross Abstract: Advancing scientific understanding through mechanistic modeling requires posing the right experimental questions to yield maximally informative data.

Atlas H&E-TME: Scalable AI-Based Tissue Profiling at Expert Pathologist-Level Accuracy

arXiv:2606.12346v1 Announce Type: cross Abstract: Hematoxylin and eosin (H&E) staining is the cornerstone of histopathology, yet scalable, quantitative analysis of H&E whole-slide images (WSIs) remain

Attention by Synchronization in Coupled Oscillator Networks

arXiv:2606.12059v1 Announce Type: new Abstract: We address transformer attention on energy-constrained physical substrates. Softmax attention requires exponentiation and global reduction, operations w

researcharxiv-cs-lg

Auditing Demographic Bias in Facial Landmark Detection for Fair Human-Robot Interaction

arXiv:2604.06961v2 Announce Type: replace Abstract: Fairness in human-robot interaction critically depends on the reliability of the perceptual models that enable robots to interpret human behavior. W

safetyarxiv-cs-cv

Augmenting Molecular Language Models with Local n-gram Memory

arXiv:2606.12113v1 Announce Type: cross Abstract: Transformer-based language models for SMILES strings suffer from a locality gap: standard character-level tokenization fragments chemically meaningful

Automated Creativity Evaluation of Language Models Across Open-Ended Tasks

arXiv:2606.11762v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved remarkable progress in language understanding, reasoning, and generation, sparking growing interest in thei

Automated Mediator for Human Negotiation: Pre-Mediation via a Structured LLM Pipeline

arXiv:2606.11379v1 Announce Type: new Abstract: Pre-mediation, the preparatory phase preceding direct human negotiation, plays a critical role in achieving mutually beneficial agreements, yet is often

Automating Geometry-Intensive Compliance Checking in BIM: Graph-Based Semantic Reasoning Framework

arXiv:2606.12065v1 Announce Type: new Abstract: Automating compliance check for geometry-intensive regulations remains a significant technical bottleneck in Building Information Modeling (BIM), primar

AutoMine Solution for AV2 2026 Scenario Mining Challenge

arXiv:2606.11874v1 Announce Type: new Abstract: With the development of autonomous driving systems, mining high-value, safety-critical, and planning-relevant scenarios from large-scale driving logs ha

Autoregressive Direct Preference Optimization

arXiv:2602.09533v2 Announce Type: replace Abstract: Direct preference optimization (DPO) has emerged as a promising approach for aligning large language models (LLMs) with human preferences. However,

researcharxiv-cs-ai

AVIS: Adaptive Test-Time Scaling for Vision-Language Models

arXiv:2606.11576v1 Announce Type: cross Abstract: Modern Vision-Language Models (VLMs) benefit from chain-of-thought prompting and test-time scaling, but these gains often come with prohibitive infere

Bad things apparently come in 4’s; tweet below must be updated with the breaking @wsj news that OpenAI is contemplating drastic price cuts, …

Bad things apparently come in 4’s; tweet below must be updated with the breaking @wsj news that OpenAI is contemplating drastic price cuts, which is surely a sign of weakness. So far today • Banks to

safetygary-marcus--x

Industry

Based Grok 🤣🤣 https://x.com/i/grok/share/32212cc499ae467ebb1f8db2b77d314a

This entry references Grok, xAI's conversational AI assistant, shared through X's integrated Grok feature. The post appears to be a humorous or casual share by Elon Musk, likely demonstrating Grok's c

industryelon-musk--x

Battery detection of XRay images using transfer learning

arXiv:2606.11779v1 Announce Type: new Abstract: The need for detecting and sorting batteries is drastically increasing for many applications. This study proves the potential of transfer learning in pr

researcharxiv-cs-cv

Benchmarking Cross-Domain Audio-Visual Deception Detection

model-releasesarxiv-cs-cv

arXiv:2405.06995v4 Announce Type: replace-cross Abstract: Automated deception detection is crucial for assisting humans in accurately assessing truthfulness and identifying deceptive behavior. Convent

Benchmarking Large Language Models for Safety Data Extraction

model-releasesarxiv-cs-cl

arXiv:2606.11204v1 Announce Type: new Abstract: Accurate extraction of structured information from Safety Data Sheets (SDS) remains challenging in industrial safety due to heterogeneous document forma

Bergson: An Open Source Library for Data Attribution

arXiv:2606.11660v1 Announce Type: new Abstract: Data attribution is a promising field in interpretability that aims to explain model behavior through the influence of its training data, with applicati

researcharxiv-cs-lg

Bernstein-Schur Kernels: Random Features by Sketched Modulation and Radial Randomization

arXiv:2606.11255v1 Announce Type: new Abstract: Bernstein--Schur kernels are products of a finite-feature kernel (one with an explicit finite-dimensional feature map) and a completely monotone shift-i

researcharxiv-cs-lg

Beyond Compaction: Structured Context Eviction for Long-Horizon Agents

model-releasesarxiv-cs-cl

arXiv:2606.11213v1 Announce Type: new Abstract: We present Context Window Lifecycle (CWL), a context-management scheme that gives long-horizon LLM agents an effectively unbounded working horizon. As a

Beyond Dark Knowledge: Mixup-Based Distillation for Reliable Predictions

arXiv:2606.12171v1 Announce Type: new Abstract: Knowledge Distillation (KD) and mixup have proven effective at inducing smoothness in class boundaries; KD captures inherent class relationships in prob

researcharxiv-cs-cv

Beyond Fully Random Masking: Attention-Guided Denoising and Optimization for Diffusion Language Models

arXiv:2606.12273v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) offer an efficient alternative to autoregressive models through parallel decoding, yet existing post-training me

researcharxiv-cs-cl

Beyond representational alignment with brain-guided language models for robust reasoning

arXiv:2606.11893v1 Announce Type: cross Abstract: The correspondence between large language models (LLMs) and the neural mechanisms underlying human higher-order cognition remains insufficiently chara

Tutorials

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching

arXiv:2606.11583v1 Announce Type: new Abstract: Text-attributed graphs (TAGs) underlie real-world applications such as citation networks, social media, and e-commerce. Few-shot graph learning on TAGs

tutorialsarxiv-cs-lg

Beyond Third-Person Audits: Situated Interaction Auditing for User-Centered LLM Bias Research

arXiv:2606.12247v1 Announce Type: cross Abstract: Research on bias in large language models (LLMs) has predominantly focused on third-person audits, which study how models represent or evaluate demogr

safetyarxiv-cs-cl

BioDivergence: A Benchmark and Evaluation Framework for Hidden Contextual Contradictions in Biomedical Abstracts

arXiv:2606.11208v1 Announce Type: cross Abstract: Biomedical findings often seem to conflict across studies, but many of these differences are context-dependent rather than true contradictions. Variat

BioMamba: Domain-Adaptive Biomedical Language Models

model-releasesarxiv-cs-cl

arXiv:2408.02600v3 Announce Type: replace Abstract: Background. Biomedical language models should improve performance on biomedical text while retaining general-language-modeling fluency. For Mamba-ba

Blind Dexterous Grasping via Real2Sim2Real Tactile Policy Learning

arXiv:2606.11767v1 Announce Type: cross Abstract: Blind grasping with a dexterous hand is a crucial manipulation capability. Nevertheless, learning such tactile-only policies for real robots remains c

Bootstrapped Monitoring: Leveraging Transparent Reasoning to Oversee Stronger AI Agents

arXiv:2606.11998v1 Announce Type: new Abstract: Trusted monitoring is a cornerstone of AI control. However, as frontier models grow more capable, the increasing capabilities gap between trusted and un

agentsarxiv-cs-lg

Breaking Entropy Bounds: Accelerating RL Training via MTP with Rejection Sampling

arXiv:2606.12370v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a key component in modern large language models, yet the rollout stage remains the key bottleneck in RL trainin

agentsarxiv-cs-cl

🚨 Breaking neuroscience/evolution news! New Nature paper provides further evidence for a central hypothesis (with a long lineage) that I de…

🚨 Breaking neuroscience/evolution news! New Nature paper provides further evidence for a central hypothesis (with a long lineage) that I defended in my 2004 book, The Birth of the Mind: the evolutiona

safetygary-marcus--x

Bridging Day and Night: Unsupervised Cross-Domain Re-Identification with Synergistic Prompt and Prototype Learning

arXiv:2606.12258v1 Announce Type: new Abstract: Cross-domain day-night re-identification (ReID) is fundamentally challenged by the substantial visual appearance discrepancies between daytime and night

safetyarxiv-cs-cv

Applications

Bridging the Modality Gap in Forensic Image Retrieval

arXiv:2606.12294v1 Announce Type: new Abstract: Automated image retrieval plays an increasingly critical role in modern forensic analysis, supporting investigative workflows that rely on efficient com

applicationsarxiv-cs-cv

Bridging the Morphology Gap: Adapting VLA Models to Dexterous Manipulation via Intent-Conditioned Fine-Tuning

arXiv:2606.12109v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have demonstrated remarkable zero-shot generalization in robotic manipulation, yet the vast majority of pre-traine

Bridging the sim2real gap in the table tennis robot with a transformer-based ball states predictor

model-releasesarxiv-cs-ro

arXiv:2606.11464v1 Announce Type: new Abstract: Robotic table tennis is a representative benchmark for high-speed, closed-loop robotic control in dynamic environments, where accurate and fast predicti