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arXiv:2605.14712v1 Announce Type: cross Abstract: Robot imitation data are often multimodal: similar visual-language observations may be followed by different action chunks because human demonstrators

arXiv:2605.14831v1 Announce Type: new Abstract: One of the bottlenecks on the way towards recursively self-improving systems is the challenge of interestingness: the ability to prospectively identify

Introducing Gemma-4-31B-it-Pearl on Together AI, Pearl Research Labs’ instruction-tuned checkpoint of Gemma 4 31B powered by @prlnet Proof of Useful Work protocol. AI natives can now use this Pearl mo

arXiv:2605.13851v1 Announce Type: new Abstract: Multi-agent orchestration -- in which a hidden coordinator manages specialized worker agents -- is becoming the default architecture for enterprise AI d

arXiv:2511.15407v3 Announce Type: replace Abstract: Humans learn by observing, interacting with environments, and internalizing physics and causality. Here, we aim to ask whether an agent can similarl

arXiv:2605.15184v1 Announce Type: new Abstract: Recent advances in Large Language Model (LLM) agents have enabled complex agentic workflows where models autonomously retrieve information, call tools,

𝕏 is the mind of humanity If you want to reach senior decision makers, most influential people, company owners, most intellectual people of the world, then the 𝕏 platform is by far the best. They are

arXiv:2602.12105v2 Announce Type: replace-cross Abstract: We propose a system for differentiating through solutions to geometry processing problems. Our system differentiates a broad class of geometri

arXiv:2605.14736v1 Announce Type: cross Abstract: Target speech extraction remains difficult for compact devices because monaural neural models lack spatial evidence and classical beamformers lose res

it almost never makes sense to use real api's for your evals. with how good coding agents have become, i will pretty much always opt to create a fake mock server for my agent to hit. the workflow is u

It has been a pleasure collaborating with the @NVIDIAAI team to ensure that Hermes Agent runs perfectly on DGX Spark! Run @NousResearch's Hermes Agent fully locally on DGX Spark. 🚀 Our newest playbook

arXiv:2510.00977v3 Announce Type: replace-cross Abstract: GRPO has emerged as a prominent reinforcement learning algorithm for post-training LLMs. Unlike critic-based methods, GRPO computes advantages

it’s kind of awesome that continual learning has now come to the agent & harness level. i remember when online learning was the big craze in traditional ml a couple of years ago, that transitioned int

arXiv:2512.12772v2 Announce Type: replace-cross Abstract: Understanding videos inherently requires reasoning over both visual and auditory information. To properly evaluate Omni-Large Language Models

𝕏 (formerly Twitter) open-sourced its 'For You' recommendation algorithm, marking a significant transparency initiative by the social platform. This move allows developers and researchers to examine h

𝕏 just open sourced the latest recommendation algorithm on GitHub 𝕏 is the only major social platform in the world to publicly open source its core recommendation algorithm It is by far the most trans

arXiv:2605.14828v1 Announce Type: cross Abstract: Existing clustering methods for functional data often prioritize partitioning accuracy over interpretability, making it challenging to extract meaning

arXiv:2509.25826v3 Announce Type: replace Abstract: Inherent temporal heterogeneity, such as varying sampling densities and periodic structures, has posed substantial challenges in zero-shot generaliz

Key ideas I picked up at the @LangChain conference this week: 'AI engineering is data science. Look at your data.' — @sh_reya & @HamelHusain 'Data strategy *before* agents.' — @AndrewYNg 'Coding agent

arXiv:2605.14123v1 Announce Type: cross Abstract: Feature sharing via split inference offers a lightweight alternative to federated learning for resource-constrained hospitals, but transmitted feature

arXiv:2605.14907v1 Announce Type: new Abstract: Knowledge graph (KG) foundation models aim to generalize across graphs with unseen entities and relations by learning transferable relational structure.

Bloomberg: Kioxia reports record Q4 earnings of ~3.8B, forecasts Q1 operating profit of ~8.2B, and says it is planning a US listing; Kioxia shares are up 300% YTD — Kioxia Holdings Corp., the world's

arXiv:2605.14062v1 Announce Type: new Abstract: While synthetic data generation with large language models (LLMs) is widely used in post-training pipelines, existing approaches typically generate full

arXiv:2605.14404v1 Announce Type: new Abstract: While LLMs are increasingly used in commercial services, they pose privacy risks such as leakage of sensitive personally identifiable information (PII).

arXiv:2605.14786v1 Announce Type: cross Abstract: As LLM-based agents increasingly browse the web on users' behalf, a natural question arises: can websites passively identify which underlying model po

arXiv:2511.07686v2 Announce Type: replace-cross Abstract: Chemical Reaction Neural Networks (CRNNs) have emerged as an interpretable machine learning framework for discovering reaction kinetics direct

arXiv:2602.11534v3 Announce Type: replace-cross Abstract: Self-attention in Transformers relies on globally normalized softmax weights, causing all tokens to compete for influence at every layer. When

arXiv:2605.14278v1 Announce Type: new Abstract: Aligning streaming autoregressive (AR) video generators with human preferences is challenging. Existing reinforcement learning methods predominantly rel

arXiv:2601.21349v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models scale neural networks by conditionally activating a small subset of experts, where the router plays a central

arXiv:2605.14527v1 Announce Type: new Abstract: Developing machine learning interatomic potentials (MLIPs) for complex materials systems remains challenging because it requires expertise in atomistic

@LangChain’s Interrupt 2026 conference was a blast!! such a pleasure to with @VictorMoreira16 about deep agents! ICYMI: we just dropped v0.6, which is focused on performance at the model, harness, and

arXiv:2605.14531v1 Announce Type: new Abstract: This work reformulates language generation as a stochastic optimal control problem, providing a unified theoretical perspective to analyze autoregressiv

arXiv:2605.14301v1 Announce Type: new Abstract: Domain adaptation faces a fundamental paradox in the cold-start regime. When target data is scarce, statistical methods fail to distinguish relevant sou

arXiv:2605.14524v1 Announce Type: cross Abstract: Recent studies have reported extit{saturation effects} and extit{multiple descent behavior} in large dimensional kernel ridge regression (KRR). Howeve

arXiv:2605.13873v1 Announce Type: cross Abstract: Web accessibility aims to ensure that web content and services are usable by people with diverse abilities. In recent years, Large Language Models (LL

arXiv:2605.14241v1 Announce Type: new Abstract: Tool-augmented LLM agents increasingly access the same tool type through multiple functionally equivalent providers, such as web-search APIs, retrievers

arXiv:2605.15054v1 Announce Type: new Abstract: Vision-language models (VLMs) have recently emerged as a promising paradigm for video anomaly detection (VAD) due to their strong visual reasoning abili

arXiv:2510.00757v3 Announce Type: replace Abstract: Graph neural networks (GNNs) largely rely on the message-passing paradigm, where nodes iteratively aggregate information from their neighbors. Yet,

arXiv:2605.14805v1 Announce Type: new Abstract: Accurate dynamics models are critical for aerial manipulators operating under complex tasks such as payload transport. However, modeling these systems r

arXiv:2605.14998v1 Announce Type: new Abstract: From subcellular structures to entire organisms, many natural systems generate complex organisation through self-organisation: local interactions that c

arXiv:2605.14832v1 Announce Type: cross Abstract: We present a flow-matching planner for autonomous driving that directly outputs actionable control trajectories defined by acceleration and curvature

arXiv:2602.21302v2 Announce Type: replace Abstract: We introduce a Task-Level Iterative Learning Control method for dynamic manipulation of ropes. We demonstrate this method on a non-planar rope manip

arXiv:2605.14539v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as an effective paradigm for improving the reasoning capabilities of large language mo

arXiv:2605.15113v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) suffers from sparse outcome signals, creating severe exploration bottlenecks on complex reasoning

arXiv:2512.02920v3 Announce Type: replace-cross Abstract: We consider analyzing traffic accident patterns using both road network data and satellite images aligned to road graph nodes. Previous work f

arXiv:2605.14494v1 Announce Type: new Abstract: Two-Stage Robust Optimization (2RO) with discrete uncertainty is challenging, often rendering exact solutions prohibitive. Scenario reduction alleviates