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“America won’t win the AI race if we beat China but end up with a CCP-style social credit system in the U.S. — and that is the danger as the…

“America won’t win the AI race if we beat China but end up with a CCP-style social credit system in the U.S. — and that is the danger as the government becomes more deeply involved in AI development a

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Analysis of the Neglect-Zero Effect in Large Language Models

DGX agent

arXiv:2606.05864v1 Announce Type: new Abstract: We investigate the extent to which the language processing of LLMs resembles human cognitive processes, focusing on a human cognitive bias called the ex

safetyarxiv-cs-cl

5 Jun 2026

Attitude-Aided Linear Calibration of Triaxial Accelerometers

arXiv:2606.06308v1 Announce Type: new Abstract: Triaxial MEMS accelerometers are widely used for inertial sensing, navigation, and sensor fusion, but existing calibration methods often rely on costly

Auditing Demonstration Curation Metrics: Action-Only Scorers Fail on the Structural Defects That Degrade Imitation Policies

arXiv:2606.05588v1 Announce Type: new Abstract: Imitation-learning policies inherit the quality of the demonstrations they are trained on, and a growing set of curation metrics promise to score and fi

Beyond Alignment: Value Diversity as a Collective Property in Multicultural Agent Systems

arXiv:2606.05985v1 Announce Type: new Abstract: Multicultural multi-agent systems are increasingly deployed in globally diverse settings, where different agents are grounded in different cultural back

Beyond Imitation: Reinforcement Learning-Based Sim-Real Co-Training for VLA Models

arXiv:2602.12628v4 Announce Type: replace Abstract: Simulation offers a scalable and low-cost way to enrich vision-language-action (VLA) training, reducing reliance on expensive real-robot demonstrati

Beyond tokens: a unified framework for latent communication in LLM-based multi-agent systems

arXiv:2606.05711v1 Announce Type: new Abstract: Multi-agent systems built on large language models (LLMs) have become a prevailing paradigm for tackling complex reasoning, planning, and tool-use tasks

'Chi nas dal soch el sent de legn' -- Auditing Text Corpora for Lombard

arXiv:2606.06349v1 Announce Type: new Abstract: Several of the world's languages are still under-resourced in terms of Natural Language Processing (NLP) tools. This is mostly due to the lack of high-q

Cosine Misleads: Auxiliary Losses Reshape Vision Language Models, Not Their Latents

arXiv:2606.05753v1 Announce Type: new Abstract: Latent visual reasoning (LVR) inserts supervised latent tokens between perception and answer generation in vision-language models (VLMs). The field uses

DexFuture: Hierarchical Future-State Visuomotor Targeting for Bimanual Dexterous Tool Use

arXiv:2606.05699v1 Announce Type: new Abstract: Bimanual dexterous tool use remains challenging for robots due to high-dimensional hand configurations and complex hand-tool-object dynamics and contact

Discrete-WAM: Unified Discrete Vision-Action Token Editing for World-Policy Learning

arXiv:2606.05645v1 Announce Type: new Abstract: Autonomous driving requires reasoning about how ego actions shape the evolution of the surrounding world. However, most end-to-end methods rely on direc

Disentangled Fine-Grained Prototype Learning for Incomplete Image-Tabular Classification

arXiv:2606.05455v1 Announce Type: new Abstract: The missing-modality problem poses a significant challenge in image-tabular multimodal learning across a wide range of multimedia applications, includin

EgoHumanoid: Unlocking In-the-Wild Loco-Manipulation with Robot-Free Egocentric Demonstration

arXiv:2602.10106v2 Announce Type: replace Abstract: Human demonstrations offer rich environmental diversity and scale naturally, making them an appealing alternative to robot teleoperation. While this

EMBER: Efficient Memory via Budgeted Evidence Retention for Long-Horizon Agents

arXiv:2606.05894v1 Announce Type: new Abstract: Long-horizon agents can archive large histories, but future answers still incur retrieval, rereading, and context costs. When retained memory misses ans

Epistemic Injustice in Language Models: An Audit of Pretraining Filters and Guardrails

arXiv:2606.05936v1 Announce Type: new Abstract: Modern language models rely on pretraining filters to remove undesirable content from training corpora and inference-time guardrails to suppress undesir

EVE: A Generator-Verifier System for Generative Policies

arXiv:2512.21430v2 Announce Type: replace Abstract: Visuomotor policies based on generative such as diffusion and flow-matching have shown strong performance for robotics applications but degrade unde

Finally, a commencement speaker who calls bullshit. Great oped by @mollyjongfast on “billionaire brain”, and why young people have a right t…

Finally, a commencement speaker who calls bullshit. Great oped by @mollyjongfast on “billionaire brain”, and why young people have a right to boo what the AI industry has become. I wrote about the com

Flow-based Policy Adaptation without Policy Updates

arXiv:2606.06461v1 Announce Type: new Abstract: Leveraging prior knowledge from pretrained policies, foundation models, or human operators offers an efficient alternative to learning robot skills from

FlowPRO: Reward-Free Reinforced Fine-Tuning of Flow-Matching VLAs via Proximalized Preference Optimization

arXiv:2606.05468v1 Announce Type: new Abstract: Post-training Vision-Language-Action (VLA) models into policies that can be reliably deployed on real robots remains a major bottleneck. SFT and DAgger

Funny how so many people read Anthropic is calling for a pause when they did NOT actually call for a pause. Read what they said, carefully. …

Funny how so many people read Anthropic is calling for a pause when they did NOT actually call for a pause. Read what they said, carefully. They want it both ways. They *don’t* actually want a pause -

Geometry-Aware Dataset Condensation for Diffusion Model Training

arXiv:2606.05883v1 Announce Type: new Abstract: Dataset condensation aims to construct compact datasets from real data via synthesis or selection. However, existing approaches are ill-suited for diffu

GLASS: GRPO-Trained LoRA for Acoustic Style Steering in Zero-Shot Text-to-Speech

arXiv:2606.05889v1 Announce Type: cross Abstract: We propose GLASS, a framework for composable acoustic style control in zero-shot autoregressive text-to-speech (TTS) that learns controls from post-ge

Grounded but Misleading: Evaluating Semantic Alignment in AI-Generated Security Explanations

arXiv:2602.05056v2 Announce Type: replace-cross Abstract: Online scams increasingly leverage fluent and context-aware social engineering strategies, creating growing demand for AI systems that explain

HERO: Learning Humanoid End-Effector Control for Visual Whole-Body Open-Vocabulary Object Grasping

arXiv:2602.16705v3 Announce Type: replace-cross Abstract: Visual loco-manipulation of arbitrary in-the-wild objects requires accurate end-effector (EE) control and a generalizable understanding of the

Human Adults and LLMs as Scientists: Who Benefits from Active Exploration?

arXiv:2606.06464v1 Announce Type: new Abstract: A long-standing finding in the causal learning literature is that adults struggle to identify conjunctive causal rules, where an effect requires the sim

IDEAL: Leveraging Infinite and Dynamic Characterizations of Large Language Models for Query-focused Summarization

arXiv:2407.10486v3 Announce Type: replace-cross Abstract: Query-focused summarization (QFS) aims to produce summaries that answer particular questions of interest, enabling greater user control and pe

Inverse Design of Realizable Metasurface based Absorbers using Improved Conditioning and Diversity Enhanced Progressively Growing GANs

arXiv:2606.05849v1 Announce Type: cross Abstract: Metasurfaces enable precise manipulation of electromagnetic waves for applications such as beam steering, sensing, and stealth technology. However, in

Inverse Manipulation through Symbolic Planning and Residual Operator Learning

arXiv:2606.05248v1 Announce Type: new Abstract: Inverting a robotic task requires more than reversing symbolic state transitions or rewinding motor trajectories. In robot manipulation tasks, symbolic

Is Diversity All You Need for Scalable Robotic Manipulation?

arXiv:2507.06219v2 Announce Type: replace Abstract: Data scaling has driven remarkable success in foundation models for Natural Language Processing (NLP) and Computer Vision (CV), yet the principles o

It was a pleasure to discuss all of these topics on @NxThompson's podcast, The Most Interesting Thing in AI. Thanks for having me on! https:…

Yoshua Bengio appeared as a guest on 'The Most Interesting Thing in AI' podcast hosted by N.X. Thompson, where he discussed various topics related to artificial intelligence. The appearance was shared

safetyyoshua-bengio--x

⚠️ Keep your eye on the ball, and don’t panic over Anthropic’s new blog. Here’s why: Anthropic is trying to strike terror into everyone’s he…

⚠️ Keep your eye on the ball, and don’t panic over Anthropic’s new blog. Here’s why: Anthropic is trying to strike terror into everyone’s hearts – “full recursive self-improvement also might increase

L-SDPPO: Policy Optimization of Spiking Diffusion Policy for Intra-vehicular Robotic Manipulation

arXiv:2606.06049v1 Announce Type: new Abstract: Intra-vehicular robots in spacecraft help reduce astronaut workload and improve mission efficiency. Recent research focuses on using deep learning metho

LadderMan: Learning Humanoid Perceptive Ladder Climbing

arXiv:2606.05873v1 Announce Type: cross Abstract: Humanoid robots hold great promise for operating in human-centered environments, yet ladder climbing remains one of the most challenging tasks due to

Large Language Models are Perplexed by some Political Parties

arXiv:2606.05937v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used, including in political applications, but their political fairness has been little studied. We assess

Latent Reasoning with Normalizing Flows

arXiv:2606.06447v1 Announce Type: new Abstract: Large language models often improve reasoning by generating explicit chain-of-thought (CoT), demonstrating the importance of intermediate computation. H

Learning Visual Spatial Planning from Symbolic State via Modality-Gap-Aware Self-Distillation

arXiv:2606.06076v1 Announce Type: cross Abstract: While vision-language models excel at general multimodal understanding, they still struggle with visual spatial planning. We attribute this to a perce

Let It Be Simple: One-Step Action Generation for Vision-Language-Action Models

arXiv:2606.05737v1 Announce Type: new Abstract: Diffusion-based vision-language-action (VLA) models often inherit the image-generation view: actions are generated by iterative denoising. We argue that

MoDex: A Diffusion Policy for Sequential Multi-Object Dexterous Grasping

arXiv:2606.05407v1 Announce Type: new Abstract: This work addresses sequentially grasping multiple objects with a single dexterous hand without releasing those already held. Most dexterous grasping me

Multi-Resolution Tactile Imitation Learning for Contact-Rich Robotic Manipulation

arXiv:2606.06281v1 Announce Type: new Abstract: Touch sensing is beneficial for solving a wide variety of manipulation tasks. While there exists a wide range of tactile sensors with different properti

not scientific, but doesn’t bode well for OpenAI. if the IPO goes badly, their luck may run out.

Gary Marcus expresses concerns that OpenAI's potential IPO performance could signal broader challenges for the company, suggesting their recent success may not be sustainable if market conditions turn

On Advantage Estimates for Max@K Policy Gradients

arXiv:2606.06080v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards is widely used for post-training reasoning models, but sparse outcome rewards make exploration difficul

OrderGrad: Optimizing Beyond the Mean with Order-Statistic Policy Gradient Estimation

arXiv:2606.06096v1 Announce Type: cross Abstract: Policy-gradient methods usually optimize expected return, but many real world applications care about distributional properties of returns: tail risk,

Ousiometrics: The essence of meaning aligns with a power-danger-structure framework instead of valence-arousal-dominance

arXiv:2110.06847v3 Announce Type: replace Abstract: From work emerging through the middle of the 20th century, the essence of meaning has become widely accepted as being described by the three orthogo

PC-Talk: Precise Facial Animation Control for Audio-Driven Talking Face Generation

arXiv:2503.14295v3 Announce Type: replace Abstract: Recent advancements in audio-driven talking face generation have made great progress in lip synchronization. However, current methods often lack suf

PiL-World: A Chunk-Wise World Model for VLA Policy-in-the-Loop Evaluation

arXiv:2606.05773v1 Announce Type: new Abstract: Vision-language-action (VLA) policies operate in a closed loop in real-world robot tasks: a robot observes the scene, executes an action chunk, and cond

Pitfalls of Evaluating Language Models with Open Benchmarks

arXiv:2507.00460v3 Announce Type: replace Abstract: Open Large Language Model (LLM) benchmarks, such as HELM and BIG-Bench, provide standardized and transparent evaluation protocols that support compa

Political appointees vetting science funding? Trump is doing to science what the Right accused previous administrations of doing. But in pre…

Political appointees vetting science funding? Trump is doing to science what the Right accused previous administrations of doing. But in previous administrations, there was no political control of res

safetyyann-lecun--x

QueryAgent-R1: Bridging Query Generation and Product Retrieval for E-Commerce Query Recommendation

arXiv:2606.05671v1 Announce Type: new Abstract: Query recommendation in e-commerce search aims to proactively suggest queries that match users' potential interests. However, existing methods mainly op