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New series from The Observer with @Yoshua_Bengio, me, and others on potential catastrophic risks in AI. (link at bottom of thread)

New series from The Observer with @Yoshua_Bengio, me, and others on potential catastrophic risks in AI. (link at bottom of thread) For the last few months I’ve been investigating how concerned we shou

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Offline Reinforcement Learning for Rotation Profile Control in Tokamaks

DGX agent

arXiv:2605.05857v2 Announce Type: replace Abstract: Tokamaks remain leading candidates for achieving practical fusion energy, yet many important control problems inside these devices are still difficu

safetyarxiv-cs-lg

10 Jun 2026

On-sky demonstration of reinforcement learning for adaptive optics control

arXiv:2606.10771v1 Announce Type: cross Abstract: Reinforcement learning (RL)-based algorithms have recently emerged as a promising approach for adaptive optics (AO) control. In simulations and labora

On the Controllability-Fidelity Frontier in Diffusion Editing

arXiv:2606.09901v1 Announce Type: cross Abstract: Diffusion-based generative models enable powerful image editing capabilities, but achieving precise control while maintaining fidelity and safety rema

One paper from three years ago has been influencing policymakers around the world about labour decisions regarding AI. What happens when the…

One paper from three years ago has been influencing policymakers around the world about labour decisions regarding AI. What happens when the gap between the evidence and new policy widens? Our report

safetycohere--x

$ORCL hit hard after hours on plan for raising even more money for AI fairytales. And this is despite the fact that [see CNBC headline on ri…

Gary Marcus critiques Oracle's after-hours stock decline following announcements of increased capital allocation toward AI initiatives, suggesting skepticism about the company's AI strategy and spendi

PADD: Path-Aligned Decompression Distillation for Non-Router Teacher to Guide MoE Student Learning

arXiv:2606.10369v1 Announce Type: new Abstract: As large language models (LLMs) continue to scale, it becomes increasingly challenging to grow model capacity under fixed computation budgets. We propos

ParaBridge: Bridging Paralinguistic Perception and Dialogue Behavior in Speech Language Models

arXiv:2606.10581v1 Announce Type: new Abstract: Speech carries more information than just words: a child's voice, a fearful tone, or a noisy background should all lead a sufficiently competent spoken-

Pareto-Guided Teacher Alignment for Fair Personalized Text Generation

arXiv:2606.10126v1 Announce Type: cross Abstract: Personalized persuasive text generation can improve relevance and engagement, but demographic conditioning may also introduce unequal framing across g

Prediction (which I have made before and which increasingly seems likely) OpenAI is gonna fall, and take a lot down with it.

Prediction (which I have made before and which increasingly seems likely) OpenAI is gonna fall, and take a lot down with it. BREAKING: SoftBank shares fall 9% after its attempt secure a $6 billion mar

Question: tech market is down about 10% over the last week. Will that affect SpaceX’s IPO? Or will everything proceed as planned, since it i…

A question posed on X regarding whether a recent 10% decline in the tech market will impact SpaceX's planned IPO timing and execution. The post, from AI researcher and entrepreneur Gary Marcus, raises

really good point. who else?

really good point. who else? BREAKING; Bill Gates just told Congress that Jeffrey Epstein had sought to use Gates’ affairs in an effort to blackmail him. So the question now is, if he did this to Bill

Reasoning or Memorization? Direction-Aware Diversity Exploration in LLM Reinforcement Learning

arXiv:2606.10346v1 Announce Type: new Abstract: Reinforcement learning has become a key paradigm for eliciting reasoning abilities in large language models, where exploration is crucial for discoverin

Reasoning over Semantic IDs Enhances Generative Recommendation

arXiv:2603.23183v2 Announce Type: replace-cross Abstract: Recent advances in generative recommendation have leveraged pretrained LLMs by formulating sequential recommendation as autoregressive generat

Recovering the Zipfian Distribution in Unsupervised Term Discovery

arXiv:2606.10781v1 Announce Type: cross Abstract: Unsupervised term discovery involves segmenting unlabelled speech into word- or syllable-like units and clustering these into a lexicon of candidate t

Representation Curriculum: Stagewise Training for Robust Ranking and Allocation

arXiv:2606.09891v1 Announce Type: cross Abstract: Ranking in digital marketplaces is a dynamic exposure-allocation mechanism: displayed items shape discovery trajectories and success events logged by

Rethinking Embodied Navigation via Relational Inductive Bias

arXiv:2606.10348v1 Announce Type: new Abstract: Object navigation requires an agent to locate a target in an unknown environment through visual observations. Existing methods typically rely on open-vo

safetyarxiv-cs-ro

RoboNaldo: Accurate, Stable and Powerful Humanoid Soccer Shooting via Motion-Guided Curriculum Reinforcement Learning

arXiv:2606.11092v1 Announce Type: cross Abstract: Elite humanoid soccer shooting requires whole-body stability, high-impulse whole-body interactions, and accuracy to targets. Motion tracking-driven re

Robust Regression of General ReLUs with Queries

arXiv:2606.11130v1 Announce Type: new Abstract: We study the task of agnostically learning general (as opposed to homogeneous) ReLUs under the Gaussian distribution with respect to the squared loss. I

Role-Agent: Bootstrapping LLM Agents via Dual-Role Evolution

arXiv:2606.10917v1 Announce Type: new Abstract: Although Large Language Model (LLM) agents have demonstrated strong performance on complex tasks, their learning is often limited by inefficient interac

SD-GRPO: Verifiable Segment Decomposition for Long-Form Vision-Language Generation

arXiv:2606.09871v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) and its variants, originally developed for Large Language Models (LLMs), have recently been applied to Multi

Selection, Not Salience: The Shape and Limits of Personalization in Social Highlighting

arXiv:2606.10398v1 Announce Type: cross Abstract: Does personalizing what a reader sees pay off, and where does it stop? Using a social web highlighter and a co-readership identity control (the same d

Selective Disk Bispectrum: A Complete and Rotation Invariant Image Descriptor

arXiv:2511.19706v2 Announce Type: replace-cross Abstract: Rotation invariance is a fundamental requirement across many computer vision tasks. Historically, this inductive bias has been encoded through

Self-Distillation Policy Optimization via Visual Feedback: Bridging Code and Visual Artifacts

arXiv:2606.10334v1 Announce Type: new Abstract: Code-generating large language models (LLMs) increasingly produce visual artifacts such as charts, web pages, and slides by writing programs that are ex

Self-EmoQ: Plutchik-Guided Value-based Planning to Drive Streaming Emotional TTS

arXiv:2606.09837v1 Announce Type: cross Abstract: Emotional interaction is increasingly crucial for conversational AI, yet current systems lack a self-emotion determination mechanism to drive the stre

Self-Supervised Relevance Modelling in Autonomous Driving via Counterfactual Analysis

arXiv:2606.10688v1 Announce Type: new Abstract: Autonomous driving relies on computationally intensive perception pipelines to continuously detect and track objects in the surrounding environment. Whi

safetyarxiv-cs-ro

SinkRec: Mitigating Semantic State Sink in Long Sequence Recommendation with Memory-Conditioned Gated Delta Networks

arXiv:2606.09888v1 Announce Type: new Abstract: Linear attention provides an efficient backbone for long-sequence recommendation by avoiding the quadratic cost of standard Transformers, but its compre

Sketch-to-Layout: A Human-Centric Computational Agent for Constraint-Aware Synthesis of Modular Photobioreactors

arXiv:2606.09849v1 Announce Type: cross Abstract: Building-integrated photobioreactors (PBRs) offer a pathway for carbon-neutral architecture, yet deployment is hindered by configuration complexity an

So far today • Banks to SoftBank: No thanks; OpenAI stock ain’t worth what you say. • Germany to Google: LLMs can be held liable • Senator W…

So far today • Banks to SoftBank: No thanks; OpenAI stock ain’t worth what you say. • Germany to Google: LLMs can be held liable • Senator Warren to SEC and SpaceX: Fix this mess; it’’s foul play to s

SocraticPO: Policy Optimization via Interactive Guidance

arXiv:2606.09887v1 Announce Type: cross Abstract: Reinforcement learning (RL) for large language models usually supervises reasoning with scalar outcome rewards, such as binary correctness. Such rewar

SoK: Colluding Adversaries in Machine Learning Pipelines

arXiv:2606.10091v1 Announce Type: cross Abstract: Machine learning (ML) models are susceptible to various security, privacy, and fairness risks. Adversaries with different characteristics (i.e., objec

Sources: Trump administration officials have told CAISI to halt publication of its model assessments while an EO President Trump signed last week is implemented (Amrith Ramkumar/Wall Street Journal)

Amrith Ramkumar / Wall Street Journal: Sources: Trump administration officials have told CAISI to halt publication of its model assessments while an EO President Trump signed last week is implemented

safetytechmeme

Speaker Group Encoding in Self-supervised Speech Recognition Models

arXiv:2606.10654v1 Announce Type: new Abstract: We investigate what self-supervised speech recognition models (S3Ms) learn about speaker groups (SGs). We examine several states of S3Ms: pretrained, fi

SpeechJBB: Probing Safety Alignment and Comprehension in Large Audio Language Models under Code-Switched Speech

arXiv:2606.06037v2 Announce Type: cross Abstract: Large audio language models (LALMs) are increasingly deployed in real-world applications, yet their safety alignment is still primarily evaluated on m

Standard Language Ideology in AI-Generated Language

arXiv:2406.08726v3 Announce Type: replace Abstract: Large language models (LLMs) generate text that reinforces standard language ideology: a bias towards certain language varieties that are granted mo

STEDiff: Strengthening Text Embedding for Text-to-Image Alignment in Diffusion Model

arXiv:2606.10653v1 Announce Type: new Abstract: Although pretrained text-to-image (T2I) generation models can produce high-quality images, they often fail to faithfully reflect the semantic intent of

Stop Early, Spend Less: Hidden-State Probes as a Practical Recipe for Streaming Moderation of LLM Outputs

arXiv:2606.10487v1 Announce Type: cross Abstract: Deploying large language models in user-facing systems requires efficient output safety filtering. Existing approaches typically rely on a separate mo

Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs

arXiv:2602.02788v2 Announce Type: replace-cross Abstract: We aim to develop physics foundation models for science and engineering that provide real-time solutions to Partial Differential Equations (PD

subtle shift: some folks seemed to have shifted from expecting truly exponential progress to being happy they can find measurable progress a…

subtle shift: some folks seemed to have shifted from expecting truly exponential progress to being happy they can find measurable progress at all. and another, even larger group has grown concerned ab

Support sufficiency as action-sufficient compression: a single-cycle rate-regret formulation

arXiv:2606.09858v1 Announce Type: cross Abstract: Robust decision-making requires compression. A system that forms a rich support state cannot usually preserve its full structure at the point of actio

Synthesizable Molecular Generation via Soft-constrained GFlowNets with Rich Chemical Priors

arXiv:2602.04119v2 Announce Type: replace Abstract: The application of generative models for experimental drug discovery campaigns is severely limited by the difficulty of designing molecules de novo

Task Robustness via Re-Labelling Vision-Action Robot Data

arXiv:2606.10918v1 Announce Type: cross Abstract: The recent trend in scaling models for robot learning has resulted in impressive policies that can perform various manipulation tasks and generalize t

TD-Grokking: Learning from Zero-Reward Problems by Training-Time Decomposition

arXiv:2606.09883v1 Announce Type: cross Abstract: Large language models (LLMs) have made remarkable progress in reasoning tasks, largely driven by post-training paradigms, especially reinforcement lea

Test-time Adversarial Takeover: A Real-time Hijacking Interface against Robotic Diffusion Policies

arXiv:2606.10371v1 Announce Type: cross Abstract: Diffusion-based action generation has become a foundational component of embodied AI, but its reliance on visual conditioning leaves deployed visuomot

Test-Time Gradient Guidance of Flow Policies in Reinforcement Learning

arXiv:2606.11087v1 Announce Type: cross Abstract: Expressive continuous control policies, such as diffusion and flow models, form the backbone of recent advances in scaling imitation learning for simu

The essay also covers what AI’s steep trajectory means for jobs and the economy, scientific progress, civil liberties, and geopolitics.

Dario Amodei's essay discusses the broad societal implications of AI's rapid advancement, examining its potential impacts across multiple domains including employment, economic disruption, accelerated

safetydario-amodei--x

The Role of Feedback Alignment in Self-Distillation

arXiv:2606.11173v1 Announce Type: new Abstract: Conditioning a language model on additional context, such as feedback on a previous attempt, typically improves its response. Self-distillation trains t

The Whale That Outswam Evolution: Swarm Intelligence Maximises Memory in Connectome Reservoirs

arXiv:2606.09902v1 Announce Type: cross Abstract: Reservoir computing exploits the fixed dynamics of a recurrent network for temporal processing, requiring only a trained linear readout. Biological ne