Knowledge catalogue
OpenAI Group PBC today released a set of features that will make it easier for nontechnical people to use its Codex automation tool. The update comes five months after Anthropic PBC added similar capa
OpenAI: OpenAI releases a new report on knowledge work: Codex now has 5M+ weekly active users, up 6x+ since February, and knowledge workers are ~20% of Codex users — OpenAI today released a new report
arXiv:2606.00419v1 Announce Type: cross Abstract: Uncertainty quantification (UQ) is critical for the deployment of machine learning predictors in real-world scenarios where the data distribution may
Tool: Pasted File Editor I really like how you can paste a large volume of text into claude.ai (or the Claude desktop/mobile apps) and it will detect it as a large paste and turn it into a file attach
arXiv:2606.01636v1 Announce Type: new Abstract: Post-training via Group Relative Policy Optimization (GRPO) has emerged as a powerful paradigm for aligning flow-based generative models with human pref
People who say this kind of thing are completely lost about what I actually said about deep learning, and I would strongly encourage them to read “Deep learning is hitting a wall” (2022). What I said
arXiv:2606.02562v1 Announce Type: cross Abstract: Autonomous robots that interact with people must make safe and efficient decisions under human-induced uncertainty, such as their preferences, goals,
arXiv:2606.00322v1 Announce Type: new Abstract: We introduce a perturbative approach for nonparametric instrumental variable (NPIV) estimation. By drawing inspiration from perturbation theory in physi
arXiv:2602.16745v2 Announce Type: replace-cross Abstract: Test-time scaling can improve model performance by aggregating stochastic reasoning trajectories. However, achieving sample-efficient test-tim
arXiv:2606.01179v1 Announce Type: cross Abstract: Entropy production governs irreversibility and uncertainty in both physical and information-theoretic systems. While Physics-Informed Neural Networks
PixelDiT is a 1.3B parameter diffusion transformer model that generates images directly in pixel space without requiring a VAE (Variational Autoencoder), representing an alternative approach to tradit
arXiv:2606.00002v1 Announce Type: new Abstract: Mixed-Integer Linear Programming (MILP) decision engines routinely output nominally optimal plans for high-stakes industrial systems. Yet deployment rar
arXiv:2606.00395v1 Announce Type: cross Abstract: Mixture of Experts (MoE) Large Language Models (LLMs) achieve strong performance at scale. However, reinforcement learning (RL) on MoE-based LLMs ofte
arXiv:2606.00984v1 Announce Type: cross Abstract: We study linear contextual bandits under rare parameter updates: the learner may incorporate reward feedback into its parameter estimate only at a sma
OpenAI announced a sales plugin for Codex that streamlines sales preparation and improves selling strategies through AI-assisted tools. The plugin leverages Codex's code generation capabilities to hel
arXiv:2506.09035v2 Announce Type: replace Abstract: We introduce Princeton365, a large-scale diverse dataset of 365 videos with accurate camera pose. Our dataset bridges the gap between accuracy and d
arXiv:2606.01908v1 Announce Type: cross Abstract: Test-time adaptation (TTA) can reduce error on new and different data by updating the model on these inputs during inference. However, these updates r
arXiv:2606.00555v1 Announce Type: new Abstract: Structure-based drug design increasingly employs LLM agents to iteratively refine ligands against a target pocket, yet a viable ligand must satisfy two
Prompting agents to 'do better' is unreliable 🙅 Giving them a rubric, a grader, and a correction loop is much closer to how you get your agent do what you want! Similar to /goal in Claude Code or othe
arXiv:2606.01665v1 Announce Type: new Abstract: We quantify the energy floor -- the minimum achievable cost given action space constraints -- for Soft Actor-Critic (SAC) HVAC control on the sbsim cali
arXiv:2606.00369v1 Announce Type: cross Abstract: Safe global deployment of AI models requires alignment with human values that vary across cultures. Yet rater pools in safety evaluation datasets rema
arXiv:2606.01291v1 Announce Type: cross Abstract: Training Variational Quantum Circuits (VQCs) under Noisy Intermediate-Scale Quantum (NISQ) constraints introduces severe computational limitations: cl
arXiv:2501.08640v2 Announce Type: replace Abstract: We propose a way to bound the generalisation errors of several classes of quantum reservoirs using the Rademacher complexity. We give specific, para
arXiv:2606.02506v1 Announce Type: new Abstract: The VRR-QA challenge evaluates visual relational reasoning in videos, where answers often depend on implicit spatial relations, event boundaries, target
arXiv:2606.01697v1 Announce Type: new Abstract: Conversational search has become increasingly important in retrieval-augmented generation (RAG) systems, where users interact with AI assistants through
arXiv:2506.01226v3 Announce Type: replace-cross Abstract: We study parameterizations of stabilizing nonlinear policies for learning-based control. We propose a structure based on a nonlinear version o
arXiv:2606.00299v1 Announce Type: cross Abstract: While Video Diffusion Models (VDMs) excel at synthesizing high-fidelity videos, enabling precise camera and scene control remains challenging. Existin
arXiv:2310.15676v2 Announce Type: replace-cross Abstract: Multi-modal 3D Intelligence has gained considerable attention due to its wide applications in autonomous driving and world simulation, etc. Co
arXiv:2606.00114v1 Announce Type: new Abstract: Image semantic communication is a critical component in next-generation wireless communication systems. However, such systems typically suffer from larg
arXiv:2606.00852v1 Announce Type: cross Abstract: Printed circuit board (PCB) defect detection is challenging because many defects are small and difficult to distinguish from complex background patter
arXiv:2606.00059v1 Announce Type: cross Abstract: Informative excitation signals are critical for accurate system identification of mechatronic systems, yet classical system identification (SI) approa
Remind me, @Elonmusk, was GPT-5 really smarter than the smartest humans? @viktaur27 @Teslarati The rate of improvement from original GPT to GPT-3 is impressive. If this rate of improvement continues,
arXiv:2606.01848v1 Announce Type: new Abstract: Search-and-rescue (SAR) requires embodied agents to explore unfamiliar environments under multimodal uncertainty, perform multi-stage interactions, and
arXiv:2606.01651v1 Announce Type: new Abstract: Generative distillation significantly accelerates text-to-image (T2I) generation by compressing multi-step trajectories into few-step student models whi
arXiv:2606.01172v1 Announce Type: new Abstract: Modeling unknown latent functions from finite, irregularly sampled measurements is a recurring challenge across science and engineering. Neural processe
arXiv:2601.18115v2 Announce Type: replace Abstract: We study the problem of learning a single neuron under standard squared loss in the presence of arbitrary label noise and group-level distributional
RubricMiddleware is a LangChain feature that enables agents to verify task completion by delegating grading to a specialized subagent using predefined rubrics. This approach parallels the goal-verific
arXiv:2512.20806v3 Announce Type: replace Abstract: Ensuring the safety of language models (LMs) while maintaining their usefulness remains a critical challenge in AI alignment. Current approaches rel
arXiv:2606.00460v1 Announce Type: new Abstract: Speech-aware large language models often generalize poorly to out-of-domain settings. We propose SALSA (Speech-Aware LLM Adaptation via Learned Steering
arXiv:2601.03615v2 Announce Type: replace Abstract: Audio Language Models (ALMs) offer a promising shift towards explainable audio deepfake detections (ADD), moving beyond extit{black-box} classifiers
arXiv:2503.24183v3 Announce Type: replace Abstract: The expansion of ride-sourcing services such as Uber and Lyft has reshaped urban transportation by offering flexible, on-demand mobility via mobile
arXiv:2606.01316v1 Announce Type: new Abstract: Scientific discovery demands intelligence, perseverance, and serendipity across vast search spaces. Today, top scientific capabilities remain siloed--on
arXiv:2606.02302v1 Announce Type: cross Abstract: Autonomous LLM agents increasingly operate in stateful environments where they access tools, files, memory, and external services. While such capabili
arXiv:2601.22965v2 Announce Type: replace Abstract: Diffusion policies (DP) have demonstrated significant potential in visual navigation by capturing diverse multi-modal trajectory distributions. Howe
Harshita Mary Varghese / Reuters: Sensor Tower: ChatGPT has become the fastest app to hit 1B global MAUs by far; ChatGPT's MAUs are up 62% YoY in Q2 to date, Claude's MAUs are up 640% YoY to 56M — Ope
arXiv:2606.00702v1 Announce Type: cross Abstract: We propose to turn generalist multi-embodiment value functions into reusable models for robot design. Instead of running a new reinforcement learning
arXiv:2510.01167v2 Announce Type: replace-cross Abstract: Aligning large language models to human preferences is inherently multidimensional, yet most pipelines collapse heterogeneous signals into a s
arXiv:2606.02540v1 Announce Type: new Abstract: Agent skills occupy a privileged position in the agent workflow, as agents are expected to implicitly follow and execute them, rendering third-party ski
arXiv:2606.00822v1 Announce Type: cross Abstract: Skill-based LLM agents increasingly rely on long procedural documents, but full-document prompting wastes tokens and dilutes information critical to e
arXiv:2606.00747v1 Announce Type: cross Abstract: For low-altitude Unmanned Aerial Vehicle (UAV) autonomy, 3D spatial understanding is not merely a perception objective, but the safety interface betwe
arXiv:2606.01101v1 Announce Type: cross Abstract: The quadratic complexity of self-attention remains a bottleneck for Large Language Models (LLMs) processing ultra-long contexts. The Naive Bayes Cogni
arXiv:2606.00593v1 Announce Type: cross Abstract: Large language models are increasingly deployed as tool-augmented agents to acquire information beyond parametric knowledge. While recent work has imp
arXiv:2606.01479v1 Announce Type: new Abstract: Integrating large language models (LLMs) into text-to-speech (TTS) systems has improved speech expressiveness, yet interpretable emotional control remai
arXiv:2601.00672v2 Announce Type: replace-cross Abstract: In this paper, we study the finite element operator network (FEONet), an operator-learning method for parametric problems, originally introduc
arXiv:2606.01446v1 Announce Type: cross Abstract: Radio frequency spectrum awareness requires the ability to detect, localize, and characterize emitters in dense and contested wireless environments. I
arXiv:2606.00584v1 Announce Type: cross Abstract: This paper proposes Spectra-Guided Neural Tucker Factorization (SG-NTF) for High-Dimensional and Incomplete (HDI) tensor completion. Circumventing dis
arXiv:2606.00962v1 Announce Type: cross Abstract: Foundational agent interoperability standards, notably the Agent-to-Agent (A2A) protocol and the Model Context Protocol (MCP), have advanced multi-age
arXiv:2301.06308v2 Announce Type: replace-cross Abstract: Sharpness-aware minimization (SAM) is a training method that seeks to find flat minima in deep learning, resulting in state-of-the-art perform
arXiv:2603.03031v2 Announce Type: replace Abstract: Large Language Models (LLMs) have achieved strong complex reasoning capabilities through Chain-of-Thought (CoT) reasoning. However, their reasoning
arXiv:2606.01086v1 Announce Type: cross Abstract: Flow and diffusion models generate high-quality samples in many modalities; however, many network evaluations are required during inference due to num