Knowledge catalogue
arXiv:2604.14488v1 Announce Type: cross Abstract: In any domain where knowledge accumulates under formal authority -- law, drug regulation, software security -- a later document can formally void an e
cool new paper on self-improving agents // Self-Evolving Agent Protocol // One of the more interesting papers I read this week. (bookmark it if you are an AI dev) The paper introduces Autogenesis, a s
arXiv:2604.14454v1 Announce Type: cross Abstract: Autonomous vehicles equipped with robust onboard perception, localization, and planning still face limitations in occlusion and non-line-of-sight (NLO
arXiv:2604.15267v1 Announce Type: cross Abstract: It is increasingly important that LLM agents interact effectively and safely with other goal-pursuing agents, yet, recent works report the opposite tr
arXiv:2604.14773v1 Announce Type: new Abstract: While LLMs have demonstrated remarkable potential in Question Answering (QA), evaluating personalization remains a critical bottleneck. Existing paradig
arXiv:2512.14098v3 Announce Type: replace Abstract: Any-to-Any models are an emerging class of multimodal models that accept combinations of text and multimodal data as input and generate them as outp
Correct 99% of people really do not understand abundance as Elon describes it. The fundamental reason is that they don’t understand compound growth. Same people who would probably pick 1 million dolla
arXiv:2604.14174v1 Announce Type: new Abstract: Alignment-tuned language models frequently suppress factual log-probabilities on politically sensitive topics despite retaining the knowledge in their h
arXiv:2509.14255v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) models improve efficiency through sparse activation, but their learned gating functions provide limited insight into routin
Abhinav Parmar / Reuters: Counterpoint: India's smartphone shipments fell 3% YoY in Q1 2026, a six-year low, as price hikes weigh on sales; 80+ smartphone models saw price hikes of ~15% — India's smar
arXiv:2603.24470v2 Announce Type: replace-cross Abstract: Every year, 10 million pets enter shelters, separated from their families. Despite desperate searches by both guardians and lost animals, 70%
In support of our mission to accelerate the developer journey on Google Cloud, we built Dev Signal: a multi-agent system designed to transform raw community signals into reliable technical guidance by
arXiv:2604.14214v1 Announce Type: new Abstract: Large Language Models utilizing reasoning techniques improve task performance but incur significant latency and token costs due to verbose generation. E
arXiv:2504.16455v2 Announce Type: replace Abstract: Transformer-based networks have achieved strong performance in low-level vision tasks like image deraining by utilizing spatial or channel-wise self
arXiv:2604.14449v1 Announce Type: new Abstract: Recent advances in data-centric artificial intelligence highlight inherent limitations in object recognition datasets. One of the primary issues stems f
arXiv:2604.14532v1 Announce Type: new Abstract: Accurate prediction of future risk and disease progression in sepsis is clinically important for early warning and timely intervention in intensive care
arXiv:2604.14545v1 Announce Type: new Abstract: Visual-inertial odometry (VIO) is widely used for mobile robot localization, but its long-term accuracy degrades without global constraints. Incorporati
arXiv:2604.14651v1 Announce Type: new Abstract: Clinical language models (LMs) are increasingly applied to support clinical risk prediction from free-text notes, yet their uncertainty estimates often
arXiv:2604.14644v1 Announce Type: new Abstract: The inability to filter out in advance all potentially problematic data from the pre-training of large language models has given rise to the need for me
arXiv:2603.05493v2 Announce Type: replace Abstract: Effective robot autonomy requires motion generation that is safe, feasible, and reactive. Current methods are fragmented: fast planners output physi
arXiv:2604.14870v1 Announce Type: new Abstract: Local loss-landscape stabilization under sample growth is typically measured either pointwise or through isotropic averaging in the full parameter space
arXiv:2311.04799v2 Announce Type: replace Abstract: Pretraining language models is still a challenge for many researchers due to its substantial computational costs. As such, there is growing interest
Dairy Queen is becoming the latest fast food chain to get in on AI, as it's bringing a chatbot to dozens of its drive-thrus across the US and Canada. It aims to help speed up drive-thru service and 'e
arXiv:2510.24538v2 Announce Type: replace Abstract: Textual humor is enormously diverse and computational studies need to account for this range, including intentionally bad humor. In this paper, we c
Data Driven Agent Design with Evals & Hill Climbing Algorithms this is a mental model dump i’ve been thinking through + iterating on as we’re building self-improvement infra around agents: - mining Tr
arXiv:2604.14720v1 Announce Type: new Abstract: Myotubes are multinucleated muscle fibers serving as key model systems for studying muscle physiology, disease mechanisms, and drug responses. Mechanist
Release: datasette 1.0a28 I was upgrading Datasette Cloud to 1.0a27 and discovered a nasty collection of accidental breakages caused by changes in that alpha. This new alpha addresses those directly:
arXiv:2601.12407v2 Announce Type: replace-cross Abstract: As LLMs rapidly advance and enter real-world use, their privacy implications are increasingly important. We study an authorship de-anonymizati
arXiv:2604.14162v1 Announce Type: new Abstract: Authors often struggle to interpret peer review feedback, deriving false hope from polite comments or feeling confused by specific low scores. To invest
arXiv:2604.14552v1 Announce Type: cross Abstract: Modern datacenters increasingly rely on low-power, single-slot inference accelerators to balance performance, energy efficiency, and rack density cons
arXiv:2509.23249v4 Announce Type: replace Abstract: It is often possible to perform reduced order modelling by specifying linear subspace which accurately captures the dynamics of the system. This app
arXiv:2604.14570v1 Announce Type: new Abstract: Deepfake detectors face growing challenges in generalization as new image synthesis techniques emerge. In particular, deepfakes generated by diffusion m
arXiv:2602.22839v2 Announce Type: replace Abstract: Presentation generation requires deep content research, coherent visual design, and iterative refinement based on observation. However, existing pre
arXiv:2510.08483v2 Announce Type: replace Abstract: Parallel scaling has emerged as a powerful paradigm to enhance reasoning capabilities in large language models (LLMs) by generating multiple Chain-o
As artificial intelligence scales, AI infrastructure is becoming the deciding factor in whether enterprise AI delivers real value or stalls. AI is shifting from experimentation to unified systems wher
arXiv:2602.07618v3 Announce Type: replace Abstract: We investigate the approximation capabilities of dense neural networks. While universal approximation theorems establish that sufficiently large arc
arXiv:2604.14370v1 Announce Type: cross Abstract: AI tools increasingly guide targeted interventions in healthcare, education, and recruiting. Algorithms score individuals, trigger outreach to those a
Vercel has updated its deployment retention policies to automatically preserve active branch deployments, preventing them from being deleted even when retention limits are reached. This feature ensure
arXiv:2604.14527v1 Announce Type: new Abstract: A low cost fluorescence-based optical system is developed for detecting the presence of certain microorganisms and molecules within a diluted sample. A
arXiv:2604.14684v1 Announce Type: new Abstract: Visual prompted object detection enables interactive and flexible definition of target categories, thereby facilitating open-vocabulary detection. Since
arXiv:2601.09240v2 Announce Type: replace Abstract: Satellite videos provide continuous observations of surface dynamics but pose significant challenges for multi-object tracking (MOT), especially und
arXiv:2604.15013v1 Announce Type: new Abstract: Data-driven dexterous hand manipulation requires large-scale, physically consistent demonstration data. Simulation and video-based methods suffer from s
arXiv:2604.14314v1 Announce Type: cross Abstract: This manuscript introduces DharmaOCR Full and Lite, a pair of specialized small language models (SSLMs) for structured OCR that jointly optimize trans
arXiv:2506.13763v2 Announce Type: replace-cross Abstract: Diffusion models have achieved remarkable success in generative modeling. Despite more stable training, the loss of diffusion models is not in
arXiv:2604.15302v1 Announce Type: cross Abstract: LLM-as-judge frameworks are increasingly used for automatic NLG evaluation, yet their per-instance reliability remains poorly understood. We present a
arXiv:2604.14733v1 Announce Type: new Abstract: Regrasp planning is often required when one pick-and-place cannot transfer an object from an initial pose to a goal pose while maintaining grasp feasibi
arXiv:2604.14621v1 Announce Type: cross Abstract: Conformal prediction (CP) has attracted broad attention as a simple and flexible framework for uncertainty quantification through prediction sets. In
arXiv:2604.14652v1 Announce Type: new Abstract: Covering one third of Earth's land surface, forests are vital to global biodiversity, climate regulation, and human well-being. In Europe, forests and w
arXiv:2411.00361v4 Announce Type: replace Abstract: Hierarchical reinforcement learning (HRL) enables agents to solve complex, long-horizon tasks by decomposing them into manageable sub-tasks. However
arXiv:2604.15140v1 Announce Type: new Abstract: We introduce DiscoTrace, a method to identify the rhetorical strategies that answerers use when responding to information-seeking questions. DiscoTrace
arXiv:2604.14528v1 Announce Type: cross Abstract: Large Language Models (LLMs) achieve strong performance through extended inference-time deliberation, yet how their reasoning failures arise remains p
arXiv:2604.14228v1 Announce Type: cross Abstract: Claude Code is an agentic coding tool that can run shell commands, edit files, and call external services on behalf of the user. This study describes
arXiv:2604.15016v1 Announce Type: new Abstract: EEG foundation models (FMs) achieve strong cross-subject and cross-task generalization but impose substantial computational and memory costs that hinder
arXiv:2510.26109v4 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has significantly boosted the reasoning capability of language models (LMs). However, existing
Yohei Nakajima humorously raises a question about the potential conflict of interest and reputational consequences of selling call data from founder pitches to AI labs while continuing to operate as a
arXiv:2604.15023v1 Announce Type: new Abstract: Mobile manipulation is a fundamental capability that enables robots to interact in expansive environments such as homes and factories. Most existing app
arXiv:2511.22521v2 Announce Type: replace Abstract: Document visual question answering requires models not only to answer questions correctly, but also to precisely localize answers within complex doc
arXiv:2604.14877v1 Announce Type: new Abstract: Does reinforcement learning genuinely expand what LLM agents can do, or merely make them more reliable? For static reasoning, recent work answers the se
arXiv:2603.05957v2 Announce Type: replace-cross Abstract: Learning across domains is challenging when data cannot be centralized due to privacy or heterogeneity, which limits the ability to train a si
arXiv:2604.14815v1 Announce Type: new Abstract: In NLP classification tasks where little labeled data exists, domain fine-tuning of transformer models on unlabeled data is an established approach. In