Knowledge catalogue
arXiv:2605.28007v1 Announce Type: cross Abstract: Deep networks are powerful function approximators, but they typically store many different computations in shared weight matrices, making it difficult
arXiv:2510.15839v2 Announce Type: replace Abstract: Random Utility Models (RUMs) are a classical framework for modeling user preferences and play a key role in reward modeling for Reinforcement Learni
arXiv:2507.06999v2 Announce Type: replace-cross Abstract: Reasoning is essential for large language models (LLMs), especially in complex tasks such as mathematical problem solving. However, multimodal
arXiv:2605.28612v1 Announce Type: new Abstract: Parity functions are fundamental Boolean operations with critical applications across machine learning, cryptography, and error correction. Yet, learnin
arXiv:2605.28162v1 Announce Type: cross Abstract: Logical operations are essential for quantum computation within quantum error-correcting codes. However, discovering their physical realizations is ch
arXiv:2602.22873v2 Announce Type: replace-cross Abstract: We introduce a theoretical framework that connects multi-chart autoencoders in manifold learning with the classical theory of vector bundles a
arXiv:2605.28328v1 Announce Type: cross Abstract: When generating outputs for domains with specific validity constraints (e.g., a program should compile), LLMs often fail in a small number of focused
arXiv:2605.28513v1 Announce Type: cross Abstract: Variance reduction (VR) methods employ stochastic gradients with decreasing variance, and they have been widely applied to solve large-scale optimizat
arXiv:2605.28309v1 Announce Type: new Abstract: In large-scale benchmarking of stochastic optimization algorithms, the key challenge is no longer whether repeated runs are needed for reliability, but
arXiv:2605.27999v1 Announce Type: cross Abstract: We address the problem of learning to assign prediction tasks to one agent from a set of available human or AI agents. In particular, we focus on the
arXiv:2605.28133v1 Announce Type: new Abstract: We study the problem of learning to bid when the bidder's value is dynamic, i.e., when the current value depends on past outcomes. Specifically, we cons
arXiv:2605.28239v1 Announce Type: new Abstract: Semi-supervised referring expression segmentation (SS-RES) aims to achieve precise pixel-level language grounding under limited annotation, yet suffers
arXiv:2605.27794v1 Announce Type: cross Abstract: This paper studies adaptive targeting under network interference in a bandit setting, where treatments applied to one individual may affect others thr
arXiv:2605.27642v1 Announce Type: new Abstract: Soft prompt tuning is a parameter-efficient method for adapting LLMs to specific tasks, but suffers from a lack of interpretability. Building on recent
arXiv:2601.21167v2 Announce Type: replace Abstract: We study stochastic logistic bandits with d-dimensional action features under the simple-regret objective, where a learner uses T rounds of explorat
arXiv:2605.28213v1 Announce Type: new Abstract: LLM-based agents are increasingly used to generate GPU kernels, but they often know what optimizations to try without knowing when those optimizations a
arXiv:2410.12035v2 Announce Type: replace-cross Abstract: Several variational bounds involving importance weighting ideas generalize the Evidence Lower BOund (ELBO) for marginal likelihood optimizatio
arXiv:2605.28120v1 Announce Type: cross Abstract: Graph-based Retrieval-Augmented Generation (GraphRAG) advances flat document retrieval by structuring knowledge as relational graphs, enabling more co
arXiv:2605.28368v1 Announce Type: new Abstract: World models have enabled interactive exploration of game environments and robotic manipulation, but physical engineering remains beyond their reach: re
Lem & Douglas Adams got AI right Presciently Golem XIV (from 1981) has an illustration of the jagged frontier as explained by an AI, Golem (GENERAL OPERATOR, LONG-RANGE, ETHICALLY STABILIZED, MULTIMOD
arXiv:2602.20497v3 Announce Type: replace-cross Abstract: Diffusion models have achieved remarkable success in image and video generation tasks. However, the high computational demands of Diffusion Tr
arXiv:2605.28524v1 Announce Type: new Abstract: In recent years, Large Language Models (LLMs) have shown great capability in processing graph tasks such as fraud detection. However, most existing meth
arXiv:2605.27914v1 Announce Type: cross Abstract: Subjective evaluation of LLM behavior -- empathy, restraint, calibrated emotional tone -- is hard. Human inter-rater agreement on such qualities satur
Raphael Satter / Reuters: Letter: US Central Command says it received “threat reports concerning adversary exploitation of commercial location data” to target US personnel in war zones — U.S. forces d
Weaviate has expanded its role-based access control (RBAC) capabilities for the Weaviate Cloud console, enabling more granular permission management and user access control. This enhancement allows ad
arXiv:2505.09861v3 Announce Type: replace-cross Abstract: Data Driven Attribution, which assigns conversion credits to marketing interactions based on causal patterns learned from data, is the foundat
arXiv:2605.27413v1 Announce Type: cross Abstract: Proteins perform their biological functions through three-dimensional structures encoded by amino acid sequences, and ligand-binding protein co-design
arXiv:2509.22553v2 Announce Type: replace-cross Abstract: Causal representation learning (CRL) has garnered increasing interest from the causal inference and artificial intelligence communities due to
arXiv:2605.28721v1 Announce Type: new Abstract: Are LLM-based search agents genuinely searching, or using the web to verify what they already know? We study this question on BrowseComp with three diag
Release: llm-anthropic 0.25.1 New model: Claude Opus 4.8 (claude-opus-4.8). New -o fast 1 option for fast mode, for organizations with that feature enabled on their account. Default max_tokens for eac
arXiv:2605.27403v1 Announce Type: cross Abstract: Written reflection assignments give students valuable opportunities for critical self-assessment, meaning making, and learning processing. Additionall
arXiv:2509.23019v5 Announce Type: replace-cross Abstract: Watermarking offers a promising solution for detecting LLM-generated content, yet its robustness under realistic query-free (black-box) evasio
arXiv:2605.28760v1 Announce Type: new Abstract: Zeroth-order (ZO) fine-tuning is attractive for large language models because it replaces backpropagation with forward objective evaluations. Existing i
LLMs actually produce bullshit for many reasons, and would continue to do so (though less) even they weren’t trained on bullshit. legal citation hallucinations are a nice example where the underlying
arXiv:2506.08928v2 Announce Type: replace Abstract: Tree-based ensembles such as random forests remain the go-to for tabular data over deep learning models due to their prediction performance and comp
Local Reachy Mini conversations wireless looks like magic! You can bring your friend around the house and get WOW effect from anyone! 🔥 Thanks @andimarafioti for the blog post on how to set this up: h
arXiv:2605.27786v1 Announce Type: cross Abstract: Large language models are known to contain representational redundancy across network depth, making depth pruning an effective approach for improving
arXiv:2605.28170v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly integrated into high-stakes decision-making, the ability to reliably quantify uncertainty has become a
Jeremy Kahn / Fortune: London- and SF-based Orbital Industries, which uses its Orb model to design advanced materials and then sell them directly, raised a 50M Series B led by Plural — Orbital Industr
Jeremy Kahn / Fortune: London-based Geordie AI, which builds a security and governance platform for AI agents, raised a 30M Series A led by Balderton at an estimated 180M valuation — Geordie AI, a Lon
arXiv:2605.28109v1 Announce Type: new Abstract: Recent advances in online reinforcement learning (RL) for large language models (LLMs) have demonstrated promising performance in complex reasoning task
arXiv:2605.27787v1 Announce Type: cross Abstract: Multi-agent systems (MAS) have substantially advanced autonomous software engineering (SWE), but their growing inference energy demands raise sustaina
arXiv:2510.03534v5 Announce Type: replace-cross Abstract: We study the problem of long-term (multiple days) mapping of a river plume using multiple autonomous underwater vehicles (AUVs), focusing on t
arXiv:2605.28160v1 Announce Type: new Abstract: Existing multimodal reasoning approaches predominantly follow two paradigms: converting visual inputs into text prior to reasoning, or performing end-to
arXiv:2605.27840v1 Announce Type: cross Abstract: Audio tokenizers are fundamental to unifying audio understanding and generation. Understanding requires high-level semantics, while generation demands
This post from Rupert Lowe's account (shared via Elon Musk's platform) claims that the political movement or party 'Restore Britain' is gaining support because it prioritizes truthfulness in its messa
Loving the @latentspacepod breakdown of our Laguna M.1/XS.2 Technical Report! The Latent Space paper club just did a deep dive, and their takeaways perfectly capture what we set out to build with our
arXiv:2602.11564v2 Announce Type: replace Abstract: Recent advances in video diffusion models have significantly improved visual quality, yet ultra-high-resolution (UHR) video generation remains a for
arXiv:2605.28271v1 Announce Type: new Abstract: Object detection is an important task in computer vision, which aims to detect the objects of interest. through the given category list or query images.
arXiv:2605.27937v1 Announce Type: cross Abstract: Scintillation detectors with excellent timing resolution enable more precise localization of radiation sources in positron emission tomography, leadin
arXiv:2605.28296v1 Announce Type: new Abstract: In modern nuclear physics experiments, identifying events of interest is challenging for nuclear reaction studies with the active target Time Projection
arXiv:2605.28077v1 Announce Type: new Abstract: Parsing chemical reaction diagrams from scientific literature is challenging due to heterogeneous layouts, intertwined visual elements, and the difficul
arXiv:2605.28486v1 Announce Type: new Abstract: Magnetically actuated microrobots have been used as wireless, non-contact manipulation tools at microscales, making them promising for minimally invasiv
arXiv:2605.28352v1 Announce Type: new Abstract: This paper presents a magnet-based robotic skin that integrates a multilayer soft lattice with distributed Hall-effect sensor arrays and a tactile super
arXiv:2605.27960v1 Announce Type: new Abstract: Despite their popularity and success, Multimodal Large Language Models (MLLMs) often struggle to interpret images accurately, which limits their reasoni
arXiv:2605.27748v1 Announce Type: cross Abstract: Industrial visual anomaly detection is usually one-class: normal images are abundant, while defects are rare, heterogeneous, and often unavailable dur
arXiv:2602.03855v2 Announce Type: replace-cross Abstract: Inverse problems are often ill-posed and require optimization schemes with strong stability and convergence guarantees. While learning-based a
Make your agent smarter. The II-Commons skill gives your agent reliable knowledge from arxiv, PubMed & more, plug it in Repo: https://github.com/Intelligent-Internet/II-Commons-Skills Add it to II-Age
Managed Deep Agents lets you create a managed Deep Agent without standing up a custom agent server. Our runtime supports: ✅ Durable threads ✅ Streaming runs ✅ Checkpointing ✅ Human-in-the-loop workflo
arXiv:2503.04863v2 Announce Type: replace-cross Abstract: Compared with voxel-based grid prediction, in the field of 3D semantic occupation prediction for autonomous driving, GaussianFormer proposed u