Knowledge catalogue
arXiv:2607.02142v1 Announce Type: cross Abstract: Alzheimers disease (AD) is a brain disorder that develops slowly and mainly affects memory, thinking, language, and daily activities. It is one of the
arXiv:2607.02206v1 Announce Type: cross Abstract: Predictions are increasingly used to guide high-stakes decisions, from treatment selection to policy making. To ensure reliability with imperfect pred
arXiv:2607.02124v1 Announce Type: new Abstract: Conventional traction control architectures intervene only after the adhesion limit of a tire has already been breached. This paper investigates whether
arXiv:2602.20459v2 Announce Type: replace Abstract: Can AI systems trained on the existing scientific record forecast the advances that will follow? We introduce PreScience, a dataset and benchmark fo
arXiv:2607.02187v1 Announce Type: new Abstract: Distributed machine learning enables collaborative model training without centralizing data, but it also exposes learning processes to privacy leakage a
arXiv:2607.01966v1 Announce Type: new Abstract: Low-voltage load forecasting is an important component in current and future energy systems with a high degree of electrification and decentralized gene
arXiv:2607.02140v1 Announce Type: new Abstract: Chemical language models (CLMs) are trained with linearized representations such as SMILES, yet it remains unclear which chemically meaningful substruct
arXiv:2512.22227v3 Announce Type: replace Abstract: We investigate whether graded states of mind form spectrum-like structure in transformer representation spaces. To do so, we construct a dataset of
arXiv:2607.01759v1 Announce Type: cross Abstract: Open-vocabulary object detection aims to localize and classify objects beyond the fixed set of categories seen dur ing training. Recent open-vocabular
arXiv:2607.01480v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR), along with recent selfdistillation variants such as SDPO, evaluates each rollout against a verifi
arXiv:2607.01610v1 Announce Type: new Abstract: Counterfactual explanation (CE) is widely used to enhance the interpretability of machine learning models and support data-driven decision-making based
arXiv:2607.02512v1 Announce Type: cross Abstract: Many everyday programming tasks resist clean rule-based implementation, such as alerting on important log lines, repairing malformed JSON, or ranking
Project Hail Mary is now on Prime Video, free for Prime members everywhere. It’s my favorite movie that I've seen in a long time. Truly outstanding and unique. Phil Lord and Chris Miller pulled off so
arXiv:2607.02057v1 Announce Type: cross Abstract: In recent years, it has become increasingly evident that large language models (LLMs) and autonomous agents raise the level of abstraction in software
Prompt engineering is costing you money. Learn how to fine-tune your models. Stuffing a lot of text into every single API call slows down your app because the model has to process all those tokens bef
arXiv:2607.01240v1 Announce Type: cross Abstract: Count-based F1 is widely used as a proxy for LLM error-detection quality, but this paper shows that it can rise dramatically without a corresponding i
arXiv:2601.03946v3 Announce Type: replace-cross Abstract: We consider the densest submatrix problem, which seeks the submatrix of fixed size of a given binary matrix that contains the most nonzero ent
arXiv:2607.01602v1 Announce Type: new Abstract: SRAM-based FPGAs provide an attractive platform for energy- and latency-constrained CNN inference at the network edge, yet transient faults can lead to
arXiv:2510.04391v5 Announce Type: replace Abstract: Mental imagery vividness is a stable individual trait, yet whether imagined scenarios share relational structure across human and synthetic large la
arXiv:2510.04484v2 Announce Type: replace-cross Abstract: The ability to control LLMs' emulated emotional states and personality traits is an essential step in enabling rich, human-centered interactio
arXiv:2607.02234v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) has emerged as a promising paradigm for improving LLM reasoning, where a privileged teacher with access to reference
arXiv:2607.02413v1 Announce Type: cross Abstract: Here we describe the quantum gas analysis and inference (Q-GAIN) Python package, which enables rapid deployment of machine learning (ML) and physics-i
arXiv:2607.02426v1 Announce Type: cross Abstract: Federated learning (FL) enables collaborative model training across distributed devices without sharing raw data, making it suitable for privacy-sensi
arXiv:2602.10431v4 Announce Type: replace Abstract: Large language models (LLMs) demand substantial computational and memory resources, posing challenges for efficient deployment. Two complementary ap
arXiv:2607.02474v1 Announce Type: new Abstract: This paper presents QuadRocket, a quadrotor-based rocket prototype that provides a low-cost, low-risk platform for validating advanced thrust-vector con
arXiv:2607.01527v1 Announce Type: cross Abstract: Room embeddings derived from reverberant speech are often unreliable: speech content and recording degradation can alter the representation even when
arXiv:2607.01731v1 Announce Type: cross Abstract: This study provides a theoretical expansion of the recent Data Relativistic Uncertainty (DRU) framework by formalizing a physics-to-AI paradigm for im
I just launched my third course, Whimsical Animations, and so far, it’s on track to sell roughly ⅓ as many copies as a typical course launch. It’s a similar story with my two existing courses. Sales a
arXiv:2607.02185v1 Announce Type: cross Abstract: Deep learning has achieved remarkable performance in medical image segmentation, yet it suffers from critical limitations: mathematical intractability
arXiv:2607.01897v1 Announce Type: cross Abstract: We introduce Rank-Then-Act (RTA), a framework for learning control policies from expert video demonstrations without environment rewards. RTA trains a
arXiv:2607.01329v1 Announce Type: cross Abstract: The geometric and topological structure of quantum cost landscapes (QCLs) governs the optimization and thus the predictive power of variational quantu
This is a discussion about token economics, likely covering how tokens function as units of value or utility in blockchain and AI systems, shared by Vipul Ved on X (formerly Twitter) and referenced by
arXiv:2607.02298v1 Announce Type: new Abstract: Autonomous drones are rapidly transforming modern warfare and civil applications alike. This paper presents the development of an integrated intelligent
arXiv:2607.02436v1 Announce Type: cross Abstract: Agentic coding assistants are increasingly given extra capabilities, such as browser based testing tools and design oriented system prompts, on the as
arXiv:2607.02504v1 Announce Type: cross Abstract: Long-form TV dramas present a formidable challenge for comprehensive video understanding, where deciphering complex storyline often relies on extbf{sp
arXiv:2607.02509v1 Announce Type: new Abstract: Understanding and reasoning over long contexts has become a key requirement for deploying large language models (LLMs) in realistic applications. Althou
Recorded an impromptu podcast episode with @swyx for @latentspacepod last month at @aiDotEngineer SG. Covered good ground including: - Why 'second brain' is the killer agent use case - Messaging platf
arXiv:2603.02112v2 Announce Type: replace-cross Abstract: Modern language models reason within bounded context, an inherent constraint that poses a fundamental barrier to long-horizon reasoning. We id
arXiv:2507.22063v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) for code generation (i.e., Code LLMs) have demonstrated impressive capabilities in AI-assisted software developme
arXiv:2607.01734v1 Announce Type: new Abstract: We present a case study in reformalization, a variant of autoformalization in which the input proof is not natural language but a formal development in
arXiv:2607.01895v1 Announce Type: new Abstract: We study ridge-regularized log-density-ratio estimation in the Gaussian location model with a common covariance matrix. By affine invariance, the model
arXiv:2607.01767v1 Announce Type: new Abstract: As agent planning moves from short tool chains toward persistent workflows with thousands or tens of thousands of steps, failures will occur inside larg
arXiv:2603.06001v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models enable robots to perform manipulation tasks directly from natural language instructions and are increasing
arXiv:2607.01903v1 Announce Type: new Abstract: LLM-integrated applications blend natural language prompts with program code, and much of their runtime behavior originates in the prompt layer rather t
arXiv:2607.01395v1 Announce Type: cross Abstract: At the heart of human visual perception lies the ability to maintain a continuous and coherent understanding of the external world. By integrating obs
arXiv:2607.01902v1 Announce Type: cross Abstract: Reliable confidence estimates are essential in semantic segmentation, especially in safety-critical settings where overconfident errors can mislead do
arXiv:2607.01733v1 Announce Type: new Abstract: Speech-LLM integration has shown promising results by leveraging extensive textual pretraining, yet its specific benefits for automatic speech recogniti
arXiv:2607.01511v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning has emerged as an effective approach for activating latent reasoning capabilities in large language models. However, mo
arXiv:2607.01665v1 Announce Type: new Abstract: Decentralized online convex optimization (D-OCO) is a popular framework for distributed applications with streaming data. To tackle the communication bo
arXiv:2607.01421v1 Announce Type: cross Abstract: Engineering management research has produced mature frameworks for software risk: ownership by feature, escalation by severity, and assurance by test
arXiv:2607.01522v1 Announce Type: cross Abstract: Mode shape recognition is a fundamental task in automotive NVH development, yet it remains dependent on manual visual inspection by experienced engine
arXiv:2607.01951v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly consulted on contested scientific questions, raising the concern that they will sycophantically retreat
arXiv:2607.01915v1 Announce Type: cross Abstract: This paper proposes a robust image processing framework for underwater robot-based construction environment monitoring, targeting complex degradations
India's first space unicorn is preparing for its first orbital launch , with Skyroot Aerospace developing the Vikram series of launch vehicles . In 2025, SpaceX posted a net loss of $4.9 billion , hig
arXiv:2607.01762v1 Announce Type: new Abstract: Many representation learning problems involve directed relations, such as lexical entailment, sentence entailment, ontology hierarchy, and citation link
arXiv:2607.01293v1 Announce Type: new Abstract: We present RuleChef, a framework that uses large language models (LLMs) to generate executable rules for NLP tasks such as text classification, Named En
arXiv:2607.01388v1 Announce Type: new Abstract: Multi-step symbolic reasoning is essential for robust financial analysis, yet most benchmarks neglect intermediate reasoning steps. FINCHAIN introduced
arXiv:2607.02063v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) have been widely used to capture spatial functional connectivity patterns to improve electroencephalography (EEG)-based d
arXiv:2607.01876v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable progress in multimodal understanding, yet their enormous parameter scale and cross-modal
arXiv:2607.01901v1 Announce Type: cross Abstract: Effective brain disease diagnosis requires the synergy of brain connectivity patterns and high-level semantic knowledge. Existing methods, however, la