Knowledge catalogue
arXiv:2605.12228v1 Announce Type: new Abstract: Mobile manipulation requires coordinated control of high-dimensional, bimanual robots. Imitation learning methods have been broadly used to solve these
Mother's Day may have passed, but we're not done showcasing mothers who build on Replit. When Noni started a family, she put her dream of building apps on hold. A busy home, a busy classroom, and no t
arXiv:2501.02955v2 Announce Type: replace Abstract: In recent years, vision language models (VLMs) have made significant advancements in video understanding. However, a crucial capability - fine-grain
arXiv:2605.05680v2 Announce Type: replace Abstract: This paper studies full-body 3D human motion recovery from head-mounted device signals. Existing diffusion-based methods often rely on global distri
arXiv:2605.11336v1 Announce Type: cross Abstract: Web search queries concern place far more often than existing labelling schemes suggest, yet the landscape of geospatial web search queries - what peo
arXiv:2605.11204v1 Announce Type: cross Abstract: Local interaction laws governing multi-agent systems can be difficult to recover from trajectory data, even when the dynamics are observed faithfully.
arXiv:2605.12134v1 Announce Type: new Abstract: Recent text-to-image models produce high-quality images, yet text ambiguity hinders precise control when specific styles or objects are required. There
arXiv:2509.21711v2 Announce Type: replace-cross Abstract: As data collection and simulation capabilities advance, multi-modal learning, the task of learning from multiple modalities and sources of dat
arXiv:2605.11530v1 Announce Type: new Abstract: Single-model ensembles (SMEs) have attracted attention as a way to approximate some of the benefits of deep ensembles within a single network. However,
arXiv:2605.12460v1 Announce Type: cross Abstract: The continued improvements in language model capability have unlocked their widespread use as drivers of autonomous agents, for example in coding or c
arXiv:2605.12176v1 Announce Type: new Abstract: This paper presents the Constrained Multi-Task Representation Learning (CMTRL) framework for linear bandits. We consider T linear bandit tasks in a d di
arXiv:2605.11835v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) promise low-power event-driven computation for temporally rich tasks, but commonly used neuron models often trade off g
arXiv:2605.12341v1 Announce Type: cross Abstract: Conformal prediction constructs prediction sets with finite-sample coverage guarantees, but its calibration stage is structurally constrained to a sca
arXiv:2605.11959v1 Announce Type: cross Abstract: Multimodal video summarization requires visual features that align semantically with language generation. Traditional approaches rely on CNN features
arXiv:2605.11181v1 Announce Type: new Abstract: The recent empirical success of the Muon optimizer has renewed interest in non-Euclidean optimization, typically justified by similarities with second-o
arXiv:2605.11396v1 Announce Type: new Abstract: The Muon optimizer has emerged as a compelling alternative to Adam for training large language models, achieving remarkable computational savings throug
Bloomberg: Musk v. Altman: Microsoft executive Michael Wetter testifies that Microsoft has spent 100B+ on OpenAI, including its investments and to build infrastructure — Microsoft Corp. has spent more
AI Security Institute: Mythos Preview is the first AI model to complete both of AISI's cyber ranges, which measure models' cyberattack capabilities; GPT-5.5 solved only one of them — In February 2026,
NASA is moving quickly to define next year's Artemis III mission in Earth orbit, a crewed flight that will test rendezvous and docking capabilities between the agency's Orion spacecraft and commercial
arXiv:2302.12039v2 Announce Type: replace Abstract: We summarize the current state of the field of NLP & Law with a specific focus on recent technical and substantive developments. To support our anal
arXiv:2605.11665v1 Announce Type: new Abstract: Robot learning research is fragmented across policy families, benchmark suites, and real robots; each implementation is entangled with the others in a c
arXiv:2605.11762v1 Announce Type: new Abstract: Learning robust navigation policies remains a core challenge in robotics. Offline imitation learning suffers from distribution shift and compounding err
Dutch artificial intelligence infrastructure giant Nebius Group N.V. said today it’s recruiting the core engineering team from AI orchestration software firm Clarifai Inc. in an effort to boost its ma
Emma Roth / The Verge: Netflix says its ad tier now has 250M monthly active viewers, up from 94M in 2025, and is expanding to 15 new countries, as it tests an ad personalization tool — The streaming s
arXiv:2509.06697v2 Announce Type: replace-cross Abstract: Accurate forecasting of exchange rates remains a persistent challenge, particularly for emerging economies such as Brazil, Russia, India, and
arXiv:2605.12343v1 Announce Type: new Abstract: Most learned PDE solvers follow a global-surrogate paradigm: a neural operator is trained to map full problem descriptions to full solution fields for a
arXiv:2605.11327v1 Announce Type: new Abstract: Classical deep learning typically operates on individual cases. Despite its success, real-world usage often requires repeated inference to estimate stat
New paper in Nature. The more a government controls its domestic media, the more it dominates AI training data, the more pro-regime outputs we get from AI. By scraping the open web, LLMs are unwitting
New paper: research agenda for secret loyalties Imagine a frontier model that has been trained to covertly advance a specific actor's interests (a nation-state, a CEO, an adversary). @joemkwon argues
arXiv:2605.11102v1 Announce Type: new Abstract: Neural warm starts can sharply reduce the number of Newton-Raphson iterations required to solve the AC power flow problem, but existing supervised appro
arXiv:2605.11583v1 Announce Type: cross Abstract: Modern low-field magnetic resonance imaging (MRI) technology offers a compelling alternative to standard high-field MRI, with portable, low-cost syste
Gary Marcus argues that current large language models (LLMs) do not constitute artificial general intelligence (AGI), though they will cause some job displacement. He suggests that true AGI, if achiev
arXiv:2605.12233v1 Announce Type: new Abstract: Terminal agents are increasingly capable of executing complex, long-horizon tasks autonomously from a single user prompt. To do so, they must interpret
no remorse, just further evasion. so slick; so dangerous. 🚨 SEVEN OPENAI INSIDERS HAVE ACCUSED SAM ALTMAN OF LYING Today on cross, Musk's lawyer walked Altman through all of them: >Ilya Sutskever (co-
arXiv:2605.11970v1 Announce Type: new Abstract: Most dimensionality reduction methods treat data as discrete point clouds, ignoring the continuous domain structure inherent to many real-world processe
arXiv:2605.12207v1 Announce Type: cross Abstract: We study the extit{parameter placement problem}: given a fixed budget of k trainable entries within the B matrix of a LoRA adapter (A frozen), does th
Not to mention 7 blog posts dropped today, including a new Deep Agents version with significant improvements… Especially excited about the Code Interpreter feature which is a sneaky powerful feature e
arXiv:2603.27358v2 Announce Type: replace Abstract: Despite a long tradition of work on extractive summarization, which by nature aims to recover the most important propositions in a text, little work
Reinforcement-learning agents — AI systems that learn by trial and error — can convert computation into new knowledge. That’s the focus of a new engineering-level collaboration between NVIDIA and Inef
NVIDIA Nemotron models received native support integration in Deep Agents version 0.6, enabling improved language model capabilities within the LangChain framework. This update allows developers to le
Observability going from 'read the traces' to 'the traces read themselves and tell you what to fix.' That's the feedback loop most agent teams are missing. 🚀Launching: LangSmith Engine LangSmith Engin
Sam Tabahriti / Reuters: Ofcom fines an unnamed suicide forum £950K, the largest OSA fine so far, for hosting illegal content accessible in the UK; the forum is linked to 130+ deaths — Britain's commu
arXiv:2603.18702v3 Announce Type: replace Abstract: We study off-policy learning (OPL) in contextual bandits, which plays a key role in a wide range of real-world applications such as recommendation s
Off to an amazing start at @LangChain Interrupt 🪁🦜 Including: 📣 Shoutout from @hwchase17 during the opening keynote! 🪁 CopilotKit booth with the best staff, demos and merch 🍸 Agents After Dark Happy H
arXiv:2505.17506v2 Announce Type: replace-cross Abstract: We study offline constrained reinforcement learning with general function approximation in discounted constrained Markov decision processes. P
arXiv:2605.11479v1 Announce Type: new Abstract: Policy evaluation is a fundamental component of the development and deployment pipeline for robotic policies. In modern manipulation systems, this probl
arXiv:2605.12400v1 Announce Type: new Abstract: We study {on-policy self-distillation} (OPSD), where a language model improves its reasoning ability by distilling privileged teacher distributions alon
arXiv:2605.12038v1 Announce Type: new Abstract: Cross-embodiment video generation aims to transfer motions across different humanoid embodiments, such as human-to-robot and robot-to-robot, enabling sc
arXiv:2605.12480v1 Announce Type: new Abstract: Recent advances in joint audio-video generation have been remarkable, yet real-world applications demand strong per-modality fidelity, cross-modal align
arXiv:2605.11629v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) have shown strong chain-of-thought (CoT) reasoning ability on vision-language tasks, but their direct de
Elon Musk posted on X about traveling to Beijing aboard Air Force One, indicating a trip to China's capital. The post suggests either an official government delegation or a significant business visit
arXiv:2605.11978v1 Announce Type: new Abstract: The performance of Large Language Models (LLMs) on downstream tasks is fundamentally constrained by the capabilities acquired during pre-training. Howev
arXiv:2605.11051v1 Announce Type: cross Abstract: LLM-based Software Engineering agents face a critical bottleneck: context length limitations cause failures on complex, long-horizon tasks. One promis
arXiv:2605.11471v1 Announce Type: new Abstract: Matrix product operator Born machines (MPO-BMs) are tractable tensor-network models for probabilistic modeling, but their efficient approximation capabi
arXiv:2605.12206v1 Announce Type: new Abstract: In reinforcement learning (RL), agents acting in partially observable Markov decision processes (POMDPs) must rely on memory, typically encoded in a rec
arXiv:2605.12168v1 Announce Type: new Abstract: Artificial intelligence systems typically rely on large, centrally collected datasets, a premise that does not hold in many real-world domains such as h
One of the biggest challenges with agents is that they produce way more than just tokens. Tool calls. State updates. Intermediate reasoning. Subagent progress. File changes. Custom events. Structured
arXiv:2605.11755v1 Announce Type: cross Abstract: Diffusion models and flow-based methods have shown impressive generative capability, especially for images, but their sampling is expensive because it
arXiv:2605.05630v2 Announce Type: replace Abstract: Hidden malicious intent in multi-turn dialogue poses a growing threat to deployed large language models (LLMs). Rather than exposing a harmful objec
arXiv:2605.11742v1 Announce Type: new Abstract: Online Continual Learning (OCL) aims to learn from endless nonext{-}stationary data streams, yet most existing methods assume a flat label space and ove