Knowledge catalogue
This post references two individuals, @charles_irl and @swyx, creating positive social energy or engaging content together on a specific occasion. Without access to the full post content, it likely do
arXiv:2606.30356v1 Announce Type: new Abstract: We propose Online Latent prediction with Invariant Views and rEconstruction (OLIVE), a self-supervised speech representation learning framework that joi
Data center coolant monitoring startup Omen AI Inc. is trying to fix one of the most pressing yet little-known challenges in the artificial intelligence industry after raising 31 million in Series A f
Tim Fernholz / TechCrunch: Omen AI, which provides real-time coolant health monitoring for data centers, raised a 31M Series A led by Nava Ventures, bringing its total funding to 41.5M — The AI-driven
arXiv:2606.30378v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated promising spatial reasoning capabilities, while these abilities remain underexplored in the e
arXiv:2606.30019v1 Announce Type: new Abstract: Music-driven dance video generation aims to synthesize expressive human motion that is temporally aligned with music while maintaining high visual fidel
arXiv:2606.28795v1 Announce Type: new Abstract: Machine Learning (ML) algorithms, such as k-Nearest Neighbours (kNN) or random forest, eschew the ideal of true data models in favour of predictive perf
On FrontierCode (Extended), our benchmark for real-world engineering tasks that grades mergeability and quality, Sonnet 5 scores 53.8% and has a 57.6% pass rate (higher than Opus 4.8). Note: These rel
arXiv:2606.19147v2 Announce Type: replace-cross Abstract: We develop finite-sample certificates for local population-risk increments (Pelta_v=R(heta_0+v)-R(heta_0)), (vinmathcal D). The primitive obje
arXiv:2606.28996v1 Announce Type: new Abstract: Short-fiber thermoplastic (SFT) composites are increasingly employed in lightweight aerospace and automotive structures owing to their favorable strengt
arXiv:2606.28864v1 Announce Type: new Abstract: Test-time scaling is a paradigm where large models use additional compute at inference to achieve better performance, without changing model weights. Wh
arXiv:2606.30498v1 Announce Type: cross Abstract: Human decision-making interprets the world through high-level concepts, such as recognizing a bird by its belly color. To bridge the gap between opaqu
arXiv:2606.29123v1 Announce Type: new Abstract: In aided inertial navigation, measurements from different sensors are often subject to unknown relative time delays. Consider a single aiding sensor who
arXiv:2606.28413v1 Announce Type: cross Abstract: A mesh of sovereign agents has no center: no shared clock, no shared model, and no coordinator to gather data or retrain. Its competence rests on each
arXiv:2606.29158v1 Announce Type: cross Abstract: Learning-rate transfer can reduce the cost of training large language models: instead of sweeping learning rates at target scale, practitioners extrap
arXiv:2606.29238v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) eliminates the learned critic in PPO by using the mean reward of grouped rollouts as a baseline. We provide a
arXiv:2606.30360v1 Announce Type: cross Abstract: The training-free integration of expert models via model merging has exposed significant security risks, enabling free-riders to combine specialized m
arXiv:2606.30084v1 Announce Type: new Abstract: MLLM-based GUI grounding methods commonly formulate target localization as autoregressive coordinate generation, enabling models to leverage the strong
arXiv:2606.29600v1 Announce Type: cross Abstract: A faithful 3D world representation should account for layered geometry, where a single camera ray may contain multiple visible and geometrically valid
arXiv:2606.30634v1 Announce Type: new Abstract: Modern large-scale LLM pretraining benefits from utilizing Pipeline Parallelism; however, synchronous implementations leave GPUs idle during pipeline bu
arXiv:2606.30077v1 Announce Type: cross Abstract: With Large Language Model (LLM) pre-training and fine-tuning shifting its focus from data volume to data quality, quality data selection has emerged a
arXiv:2603.16856v2 Announce Type: replace Abstract: The prevailing paradigm for improving large language models relies on offline training with human annotations or simulated environments, leaving the
arXiv:2502.11491v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown remarkable capabilities in natural language processing. However, in knowledge graph question answering
arXiv:2606.29786v1 Announce Type: new Abstract: 3D scene graphs (3DSGs) provide a compact and structured abstraction of 3D environments. Although advances in foundation models have enabled open-vocabu
arXiv:2606.28867v1 Announce Type: new Abstract: Creative Commons licenses dominate African NLP corpus releases, but their compatibility rules are rarely applied. CC-BY-SA and CC-BY-NC cannot be combin
arXiv:2606.30116v1 Announce Type: new Abstract: Pairwise preference data is widely used for training and evaluating language models (e.g., RLHF), but each datapoint records a choice, not the rationale
arXiv:2606.30638v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has emerged at the forefront of 3D scene reconstruction. Extending 3DGS with language-driven, open-vocabulary understanding
Swyx posted a welcome message on X (formerly Twitter), likely introducing a topic, event, or initiative. The tweet appears to be part of a broader conversation or announcement, as indicated by the URL
arXiv:2606.29936v1 Announce Type: new Abstract: Open-environment tabletop robotic manipulation requires systems to possess semantic understanding, precise geometric pose estimation, and high-frequency
arXiv:2606.28342v1 Announce Type: cross Abstract: Decentralized learning is a promising paradigm for collaborative training in mobile and pervasive systems, as it avoids a central coordinator and does
arXiv:2606.30625v1 Announce Type: cross Abstract: Contrastive embedding models trained with scale-invariant losses are typically paired with distance metrics like cosine similarity, effectively ignori
arXiv:2606.29554v1 Announce Type: new Abstract: Shuffle order can be a larger source of fine-tuning noise than a memoryless analysis predicts: fixed-clock optimizer memory makes local equal-multiset c
arXiv:2606.29717v1 Announce Type: cross Abstract: Predicting a material's properties from its structure is a central, fast-advancing problem in computational materials science. A decade of work has pr
arXiv:2606.30321v1 Announce Type: new Abstract: ICAO-compliant machine readable travel documents enable automated biometric face verification. The biometric reference is stored on an RFID chip include
arXiv:2606.29725v1 Announce Type: new Abstract: In this paper, we formulate a new vehicle dispatch optimization problem, called Nursing Care Taxi Dispatch, as a variant of the Vehicle Routing Problem,
arXiv:2407.19633v4 Announce Type: replace Abstract: Optimization problems are pervasive in sectors from manufacturing and distribution to healthcare. However, most such problems are still solved heuri
arXiv:2512.09066v2 Announce Type: replace-cross Abstract: Reliable assessment of the abilities of large audio language models (LALMs) is essential to advancing the state of the art. As benchmarks rapi
arXiv:2606.30534v1 Announce Type: new Abstract: We introduce Orca, an initial instantiation of a general world foundation model. Orca learns a unified world latent space from multimodal world signals
Ornith-1.0-35B, a 35-billion parameter model, has been made available for use through Claude Code via Hugging Face integration. This announcement indicates expanded model availability and integration
arXiv:2606.29537v1 Announce Type: new Abstract: Existing computer-use benchmarks fail to capture the realism, complexity, and long-horizon demands of real-world computer use, limiting their ability to
Josh Scott / BetaKit: Ottawa-based Dominion Dynamics, which is building software, sensors, and drones to autonomously monitor the Arctic, raised a CA139M Series A led by Georgian — Six months after cl
Our first summit dedicated to world models, coming to SF this September. Announcing our first summit dedicated to world models, coming to SF this September. Very excited to have some incredible resear
Our Founder and Chief Scientist @EdoLiberty just kicked off the Search & Retrieval track @aiDotEngineer. 'Agents don't need to be smarter. They need a Knowledge Layer.' We've got a big update on this
arXiv:2502.19460v4 Announce Type: replace-cross Abstract: Dependent censoring occurs when the event time and censoring time are not conditionally independent given the observed covariates. This compli
arXiv:2606.30421v1 Announce Type: new Abstract: Autonomous driving systems are steadily moving toward end-to-end paradigms to mitigate the limited adaptability of rule-based pipelines in complex traff
arXiv:2501.07437v3 Announce Type: replace-cross Abstract: Most statistical models for pairwise comparisons, including the Bradley-Terry (BT) and Thurstone models and many extensions, make a relatively
arXiv:2606.30015v1 Announce Type: new Abstract: Since intelligence fundamentally relies on efficient skill acquisition (Chollet, 2019), the ability to leverage skills is critical. For LLMs, skills, ma
arXiv:2606.28898v1 Announce Type: new Abstract: Knowledge updating in pre-trained Large Language Models (LLMs) remains an important challenge. While continual training provides a potential avenue for
arXiv:2606.29272v1 Announce Type: new Abstract: Technology computer-aided design (TCAD) semiconductor device simulation is fundamentally constrained by the high computational cost of iteratively solvi
arXiv:2510.19465v2 Announce Type: replace Abstract: Obtaining truly representative pore-scale images that match bulk formation properties remains a fundamental challenge in subsurface characterization
PEOPLE ARE BLAMING ELON MUSK FOR “DEATHS” FROM USAID CUTS — BUT THE DATA AND REALITY SAY OTHERWISE Opponents are loudly claiming that cutting wasteful USAID spending is killing people in poor countrie
Perforce Software Inc. today expanded its Perforce Intelligence lineup with an agentic gateway for managing artificial intelligence agents, an autonomous testing platform driven by natural language an
arXiv:2606.29556v1 Announce Type: new Abstract: We propose Persona-Trained Monte Carlo (PTMC), a method for estimating distributions of market-outcome statistics by repeatedly simulating limit-order-b
arXiv:2405.16472v2 Announce Type: replace Abstract: Contemporary AI faces the challenge of balancing generality with user-specific personalization. In federated learning (FL), this challenge is amplif
arXiv:2606.28845v1 Announce Type: new Abstract: Personalizing Multimodal Large Language Models (MLLMs) aims to recognize users' unique concepts from visual data and provide personalized responses. Alt
arXiv:2606.28854v1 Announce Type: cross Abstract: The common factor analytic model is related to Helmholtz and Boltzmann machines, can be conceived as a linear autoencoder, or can be thought of as a s
arXiv:2606.30627v1 Announce Type: cross Abstract: Conservative offline training is widely advocated as a safe foundation for subsequent online adaptation: if a policy stays close to well-supported beh
arXiv:2606.30477v1 Announce Type: new Abstract: Segment Anything Model (SAM) has revolutionized promptable image segmentation with strong zero-shot generalization. However, its performance degrades su
arXiv:2606.29340v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a reasoning model on rollouts sampled from its own policy by matching a privileged teacher that also sees veri
arXiv:2606.28667v1 Announce Type: new Abstract: Sign languages are compositional systems where meaning arises by combining sublexical phonological parameters, such as handshape, location, and movement