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Rank Collapse, Fixed Points, and the Renormalization Group Structure of MLP Residual Networks

model-releasesarxiv-cs-lg

arXiv:2606.10324v1 Announce Type: new Abstract: The analogy between deep neural network forward passes and renormalization group (RG) flows has been repeatedly noted in the literature, but existing tr

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Research

RankLLM: Weighted Ranking of LLMs by Quantifying Question Difficulty

DGX agent

arXiv:2602.12424v2 Announce Type: replace-cross Abstract: Benchmarks establish a standardized evaluation framework to systematically assess the performance of large language models (LLMs), facilitatin

researcharxiv-cs-ai

10 Jun 2026

Applications

RAPTOR: Rapid Aerial Pickup and Transport of Objects by Robots

arXiv:2203.03018v3 Announce Type: replace Abstract: Rapid aerial grasping through robots can lead to many applications that utilize fast and dynamic picking and placing of objects. Rigid grippers trad

applicationsarxiv-cs-ro

RAT: Reference-Augmented Training for ASV Anti-Spoofing

arXiv:2606.10908v1 Announce Type: cross Abstract: We introduce a spoofing countermeasure architecture conditioned on speaker-reference recordings, but observe that it converges to a solution that effe

READER: Robust Evidence-based Authorship Decoding via Extracted Representations

arXiv:2606.10794v1 Announce Type: new Abstract: As agentic applications increasingly route user tasks through official and third-party LLM APIs, provenance becomes an operational question: which model

REAL: A Reasoning-Enhanced Graph Framework for Long-Term Memory Management of LLMs

model-releasesarxiv-cs-cl

arXiv:2606.10694v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly expected to interact with users over long time horizons. However, due to their finite context window, LLMs

Really enjoyed reading the Microsoft MAI-Thinking-1 'Building a Hill Climbing Machine' paper. Amazing they publicly released all the info ne…

model-releasesyann-lecun--x

Really enjoyed reading the Microsoft MAI-Thinking-1 'Building a Hill Climbing Machine' paper. Amazing they publicly released all the info needed to train a frontier model, down to hparams. I also thou

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

safetygary-marcus--x

RealMath-Eval: Why SOTA Judges Struggle with Real Human Reasoning

arXiv:2606.10254v1 Announce Type: new Abstract: While Large Language Models (LLMs) have achieved near-perfect performance in solving high-school mathematics, their ability to evaluate the diverse reas

ReasonAlloc: Hierarchical Decoding-Time KV Cache Budget Allocation for Reasoning Models

arXiv:2606.11164v1 Announce Type: new Abstract: Long chain-of-thought (CoT) trajectories in large language model (LLM) reasoning cause severe inference bottlenecks due to rapid key-value (KV) cache gr

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

Recalling Too Well: Sycophancy Evaluation and Mitigation in Memory-Augmented Models

arXiv:2606.10949v1 Announce Type: new Abstract: Persistent memory systems promise to make LLMs more helpful by storing user beliefs over time. We show they also make models less correct by systematica

Recoverable but Not Stationary:Local Linear Structures in Weights and Activations

arXiv:2606.10929v1 Announce Type: cross Abstract: Task vectors, LoRA, activation steering, and random search around pretrained weights all suggest that learned behaviour can be controlled by linear di

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

safetyarxiv-cs-cl

Tools

recruiting two singer-researchers to stage a dramatic adaptiation of the Muon/Shampoo debate set to the tune of “Your Obedient Servant” from…

Swyx posted about recruiting singer-researchers to create a dramatic musical adaptation of the Muon/Shampoo debate, using the melody from 'Your Obedient Servant' (likely referencing the Hamilton music

toolsswyx--x

RedAct: Redacting Agent Capability Traces for Procedural Skill Protection

model-releasesarxiv-cs-cl

arXiv:2606.10813v1 Announce Type: cross Abstract: Users rely on execution traces to observe agent behavior, diagnose failures, and ensure accountability. These traces contain rich procedural detail, i

ReflectiChain: Epistemic Grounding in LLM-Driven World Models for Supply Chain Resilience

arXiv:2606.10359v1 Announce Type: new Abstract: AI agents in supply chains face a fundamental epistemic gap: large language models (LLMs) interpret policies but lack physical grounding, while reinforc

Agents

Regimes: An Auditable, Held-Out-Gated Improvement Loop Demonstrated on LongMemEval with ActiveGraph

arXiv:2606.10241v1 Announce Type: new Abstract: Autonomous improvement loops are hard to trust because the improvement process is usually external scaffolding bolted onto the agent: failures go unlogg

agentsarxiv-cs-ai

Representation-Aware Advantage Estimation: Your Reward Model Provides More Than A Scalar Output

arXiv:2606.10528v1 Announce Type: cross Abstract: Current reinforcement learning from human feedback (RLHF) methods primarily rely on scalar rewards from a trained reward model (RM). While effective,

researcharxiv-cs-cl

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

Agents

Resilient Navigation for Autonomous Farm Robots by Leveraging Jerk-Augmented Models with IMU-Only Disturbance Rejection

arXiv:2606.10971v1 Announce Type: new Abstract: Precise state estimation for navigation of autonomous agricultural robots is often compromised by sensor outages (GNSS/LiDAR/Visual) and high-frequency

agentsarxiv-cs-ro

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

Rethinking the Flow-Based Gradual Domain Adaptation: A Semi-Dual Optimal Transport Perspective

arXiv:2602.01179v2 Announce Type: replace Abstract: Gradual domain adaptation (GDA) aims to mitigate domain shift by progressively adapting models from the source domain to the target domain via inter

Revisiting Metric Reliability for Fine-grained Evaluation of Machine Translation and Summarization in Indian Languages

model-releasesarxiv-cs-cl

arXiv:2510.07061v2 Announce Type: replace Abstract: While automatic metrics drive progress in Machine Translation (MT) and Text Summarization (TS), existing metrics have been developed and validated a

Revisiting Positive Samples in Graph Contrastive Learning: From the Perspective of Message Passing

arXiv:2606.10284v1 Announce Type: new Abstract: Graph Contrastive Learning (GCL), which trains graph encoders by maximizing similarity between positive samples and minimizing it between negative ones,

Risk Comparisons in Linear Regression: Implicit Regularization Dominates Explicit Regularization

arXiv:2509.17251v2 Announce Type: replace-cross Abstract: Existing theory suggests that for linear regression problems categorized by capacity and source conditions, gradient descent (GD) is always mi

RKSC: Reasoning-Aware KV Cache Sharing and Confident Early Exit for Multi-Step LLM Inference

arXiv:2606.09937v1 Announce Type: cross Abstract: We introduce RKSC (Reasoning-Aware KV Cache Sharing), a training-free inference framework that eliminates two structural redundancies in multi-branch

researcharxiv-cs-ai

RoboGPT-R1: Enhancing Robot Task Planning with Reinforcement Learning

arXiv:2510.14828v3 Announce Type: replace Abstract: Improving the reasoning capabilities of embodied agents is crucial for robots to complete complex human instructions in long-view manipulation tasks

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

RobotEQ: Transitioning from Passive Intelligence to Active Intelligence in Embodied AI

model-releasesarxiv-cs-ro

arXiv:2605.06234v2 Announce Type: replace Abstract: Embodied AI is a prominent research topic in both academia and industry. Current research centers on completing tasks based on explicit user instruc

Robotic Nonprehensile Object Transportation with a Hanging Tray

arXiv:2606.10039v1 Announce Type: new Abstract: We consider the nonprehensile object transportation task known as the waiter's problem, in which a robot must move an object balanced on a tray from one

researcharxiv-cs-ro

Robust Active Learning for Few-Shot Example Selection in Text-to-SQL

arXiv:2606.10125v1 Announce Type: cross Abstract: Few-shot example retrieval is the dominant paradigm for grounding large language models (LLMs) in domain-specific text-to-SQL systems. However, the qu

Agents

Robust Deep Reinforcement Learning Through Adversarial Attacks and Training : A Survey

arXiv:2403.00420v3 Announce Type: replace-cross Abstract: Deep Reinforcement Learning (DRL) is a subfield of machine learning for training autonomous agents that take sequential actions across complex

agentsarxiv-cs-ai

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

safetyarxiv-cs-lg

Industry

“Rockets are cool. There's no getting around that.” — Elon Musk

Elon Musk expresses enthusiasm for rocket technology in a casual social media post, reflecting his general passion for spaceflight and space exploration. The statement represents Musk's characteristic

industryelon-musk--x

Applications

Rod models in continuum and soft robot control: a review

arXiv:2407.05886v3 Announce Type: replace Abstract: Continuum and soft robots can transform automation tasks requiring compliant interaction in constrained or unstructured environments, including heal

applicationsarxiv-cs-ro

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

ros2probe: Non-intrusive, Kernel-selective Observability for Robot Operating System 2 Middleware

arXiv:2606.10746v1 Announce Type: new Abstract: Robot Operating System 2 (ROS 2), the de facto standard middleware framework for robots, runs each robot as a graph of nodes communicating over the Data

researcharxiv-cs-ro

Rotate2Think: Geometric Priming via Orthogonal Rotation to Improve Language Model Reasoning

arXiv:2606.09873v1 Announce Type: cross Abstract: Reasoning models achieve strong performance on challenging tasks by generating explicit intermediate reasoning traces before producing a final answer.

Routing-Aware Expert Calibration for Machine Unlearning in Mixture-of-Experts Language Models

arXiv:2606.10338v1 Announce Type: cross Abstract: Machine unlearning is increasingly important for large language models, yet unlearning in Mixture-of-Experts (MoE) architectures remains underexplored

researcharxiv-cs-ai

Hardware

Run DiffusionGemma on NVIDIA for Developer-Ready, High-Throughput Text Generation

DiffusionGemma is an experimental open model built for exceptionally fast text generation that NVIDIA has optimized to run on GeForce RTX GPUs, RTX PRO, and DGX Spark systems. Rather than generating t

hardwarenvidia-developer

Local Ai

RunPod AI Hub - Public Beta 1.34 live

local-air-stablediffusion

RunPod Hub is a centralized catalog of preconfigured AI repositories that you can browse, deploy, and share, optimized for RunPod's Serverless infrastructure to deploy in minutes. The platform include

SAFE: An LLM-as-Verifier Framework for Evidence-Grounded Multi-Hop Reasoning

arXiv:2604.01993v2 Announce Type: replace-cross Abstract: Multi-hop QA benchmarks often reward Large Language Models (LLMs) for spurious correctness, where models reach correct answers through invalid

Sample Where You Struggle: Sharpening Base Model Reasoning via Entropy-Guided Power Sampling

arXiv:2606.09926v1 Announce Type: cross Abstract: Sampling from the sequence-level power distribution p^alpha elicits RL-level reasoning from base language models without any parameter updates, but th

Hardware

Sampling Triangulations and Calabi-Yau Threefolds with Autoregressive GNNs

arXiv:2605.27770v2 Announce Type: cross Abstract: We introduce `dualGNN', an autoregressive message-passing GNN for sampling fine, regular triangulations (FRTs) of convex polytopes. dualGNN operates o

hardwarearxiv-cs-lg

SARM2: Multi-Task Stage Aware Reward Modeling for Self Improving Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.10305v1 Announce Type: new Abstract: Fine-tuning vision-language-action (VLA) policies for long-horizon manipulation still relies heavily on behavior cloning, which requires costly high-qua

Tutorials

Say what you will about OpenAI but at least their employees debate their positions in public

tutorialsjeremy-howard--x

This post likely praises OpenAI's organizational culture for encouraging public discourse and debate among employees about company decisions and positions. The statement suggests that OpenAI demonstra