Knowledge catalogue
arXiv:2605.02466v1 Announce Type: new Abstract: The digitization of old encyclopedias represents an important step to improve access to historically structured knowledge. Often, however, this process
Enterprise productivity has long been measured by output and headcount, yet the tools and overhauls meant to improve it keep delivering diminishing returns. The discipline software teams quietly perfe
arXiv:2505.16850v2 Announce Type: replace-cross Abstract: Federated Learning (FL) has emerged as a promising paradigm for collaborative model training while preserving data privacy across decentralize
arXiv:2601.18569v2 Announce Type: replace-cross Abstract: In this letter, we propose an Attention-Based Neural-Augmented Kalman Filter (AttenNKF) for state estimation in legged robots. Foot slip is a
arXiv:2605.00236v1 Announce Type: cross Abstract: Safety-aligned large language models rely on RLHF and instruction tuning to refuse harmful requests, yet the internal mechanisms implementing safety b
arXiv:2602.01203v2 Announce Type: replace Abstract: Large Language Models (LLMs) often assign disproportionate attention to the first token, a phenomenon known as the attention sink. Several recent ap
arXiv:2605.01229v1 Announce Type: cross Abstract: Cross-attention patterns in neural machine translation (NMT) are widely used to study how multilingual models align linguistic structure. We report a
arXiv:2605.01480v1 Announce Type: new Abstract: We study training-free image editing on Qwen-Image-Edit-2511, a 60-block multi-modal diffusion transformer (MMDiT) that concatenates noise and source-im
arXiv:2506.13727v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are widely deployed in real-world applications, yet their internal mechanisms remain difficult to interpret and c
arXiv:2605.01451v1 Announce Type: new Abstract: Large language models (LLMs) are rapidly being integrated into high-stakes public safety systems, including emergency call triage and dispatch decision
arXiv:2605.02630v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have enabled autonomous GUI agents that translate natural language instructions into executable screen coordinates. Howeve
arXiv:2605.02567v1 Announce Type: new Abstract: The rapid advancement of generative Artificial Intelligence (AI) has introduced significant challenges for reliable AI-generated image detection. Existi
arXiv:2605.01555v1 Announce Type: new Abstract: We introduce an autonomous multiagent framework for mechanistic interpretability that automates both explaining and finding internal features in large l
arXiv:2506.03820v2 Announce Type: replace Abstract: Hausa texts are often characterized by writing anomalies, such as incorrect character substitutions and spacing errors, which sometimes hinder natur
arXiv:2605.02402v1 Announce Type: new Abstract: Reflective thinking is a key competency in education, but assessing reflective writing remains a time-consuming and subjective task for education expert
arXiv:2605.01295v1 Announce Type: new Abstract: In the pursuit of autonomous learning systems, the foundational assumption of stationarity, the premise that data distributions and model behaviors rema
arXiv:2601.06034v1 Announce Type: cross Abstract: Software testing is critical in the software development lifecycle, yet translating requirements into executable test scripts remains manual and error
arXiv:2605.00868v1 Announce Type: cross Abstract: We present a Safe Active Learning (SAL) framework for autonomous reliability characterization of rectifying Ga_2O_3-based devices under coupled therma
arXiv:2503.07557v2 Announce Type: replace Abstract: We present a novel method, AutoSpatial, an efficient approach with structured spatial grounding to enhance VLMs' spatial reasoning. By combining min
arXiv:2506.09082v5 Announce Type: replace Abstract: The rise of vision foundation models (VFMs) calls for systematic evaluation. A common approach pairs VFMs with large language models (LLMs) as gener
Available to all Max and Enterprise subscribers in Perplexity and Computer. Available only in Computer for Pro subscribers. Read about premium health sources in Perplexity and Computer in our blog: ht
arXiv:2512.10571v4 Announce Type: replace Abstract: Recent advancements in video generation highlight that realistic audio-visual synchronization is crucial for engaging content creation. However, exi
B9028 is a release build from the llama.cpp project, which provides LLM inference in C/C++. The llama.cpp project uses sequential build numbers (like b9028) to track intermediate releases of its LLM i
B9030 is a release build of llama.cpp, a C/C++ implementation for LLM inference . This build release would contain bug fixes, performance improvements, and new features added to the llama.cpp project
Release b9031 of llama.cpp optimizes backend loading by only loading backends when required, as specified in pull request #22290 . The release includes binary builds for multiple platforms including m
Release b9033 is a build of llama.cpp with a sync of ggml , published on May 5, 2026. The release provides compiled binaries across multiple platforms including macOS, Linux, Android, Windows, and ope
arXiv:2605.01876v1 Announce Type: new Abstract: Multimodal resources for non-periodic court sports with laboratory-grade sensing remain scarce: few publicly pair instrumented ground reaction force (GR
arXiv:2602.07200v2 Announce Type: replace-cross Abstract: Spiking Neural Networks (SNNs) are energy-efficient counterparts of Deep Neural Networks (DNNs) with high biological plausibility, as informat
arXiv:2507.13563v2 Announce Type: replace Abstract: We introduce Balalaika, an open-source, data-centric pipeline for processing audio and producing prosody-aware annotations. It combines semantic VAD
arXiv:2510.08599v2 Announce Type: replace-cross Abstract: Pruning large pre-trained transformers in a data-scarce scenario is challenging, as it often requires massive retraining data to recover perfo
arXiv:2605.01319v1 Announce Type: cross Abstract: Barren plateaus (BPs) are usually described by the exponential suppression of gradient variance, but the mechanism by which gradient signal disappears
arXiv:2605.01425v1 Announce Type: new Abstract: Generative AI disrupts the practice of giving credit to work that came before. Ideally, a generative model would give credit to any work on which its ou
arXiv:2507.21803v2 Announce Type: replace Abstract: Carbon Capture and Storage (CCS) stands as a pivotal technology for fostering a sustainable future. The process, which involves injecting supercriti
This quote attributed to Elon Musk on X advocates for developing personal strength and resilience against adversaries while maintaining the moral high ground through forgiveness. The statement emphasi
arXiv:2605.02620v1 Announce Type: new Abstract: Reproducing an empirical NLP study used to take weeks. Given the released data and a modern agentic-research harness, we redo every experiment of a rece
arXiv:2605.01901v1 Announce Type: new Abstract: Traffic digital twins are powerful tools for advanced traffic management, and most systems are built on static geometric representations. However, these
arXiv:2605.01322v1 Announce Type: new Abstract: This study presents a comparative analysis between two primary approaches in Natural Language Processing (NLP): Machine Learning (ML) utilizing the PyCa
arXiv:2605.01074v1 Announce Type: cross Abstract: Associative memory or content-addressable memory is an important component function in computer science and information processing, and at the same ti
arXiv:2605.02520v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) offers a well-established path to grounding large language model (LLM) outputs in external knowledge, yet the quest
arXiv:2605.01681v1 Announce Type: new Abstract: Virtual screening performance depends heavily on the chosen docking and scoring methods. Recent AI-based tools such as DiffDock and NMDN have reported s
arXiv:2605.02009v1 Announce Type: cross Abstract: Building on recent advances in representation learning for wireless channels, this work investigates the cost-benefit trade-offs of high-dimensional c
arXiv:2602.07249v2 Announce Type: replace-cross Abstract: Autonomous Vehicles (AVs), especially vision-based AVs, are rapidly being deployed without human operators. As AVs operate in safety-critical
arXiv:2605.01796v1 Announce Type: new Abstract: Confidence calibration has been dominated by the Expected Calibration Error (ECE), a linear metric that counts calibration offset equally regardless of
arXiv:2605.02284v1 Announce Type: new Abstract: Open-Set Object Detection (OSOD) is crucial for autonomous driving, where perception systems must recognize and localize both known and previously unsee
arXiv:2605.01324v1 Announce Type: new Abstract: Although reinforcement learning (RL) has significantly advanced reasoning capabilities in large multimodal language models (MLLMs), its efficacy remains
arXiv:2605.01647v1 Announce Type: new Abstract: Training-free AI text detection methods primarily rely on model log-probabilities, achieving strong performance through approaches like Binoculars and D
arXiv:2605.01302v1 Announce Type: new Abstract: Standard Retrieval-Augmented Generation (RAG) systems predominantly rely on semantic relevance as a proxy for utility. However, this assumption collapse
arXiv:2601.12024v2 Announce Type: replace-cross Abstract: Customer reviews contain valuable signals about service quality, but converting large-scale review corpora into actionable business recommenda
arXiv:2605.02528v1 Announce Type: cross Abstract: Deep reinforcement learning (DRL) navigation policies often overfit to the structure of their training environments, as environmental diversity is typ
arXiv:2605.00313v1 Announce Type: cross Abstract: The current structure-centric paradigm in artificial intelligence (AI)-driven materials discovery, despite delivering thousands of candidate structure
arXiv:2605.01289v1 Announce Type: new Abstract: This paper investigates goal-directed tracking control of underactuated blimps with center-of-mass (CoM) reconfiguration. Unlike conventional overactuat
arXiv:2605.01698v1 Announce Type: new Abstract: BIM models provide structured representations of building geometry, semantics, and topology, yet extracting specific information from them remains remar
arXiv:2605.02375v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard approach for improving reasoning in language models, yet models trained with
arXiv:2605.02660v1 Announce Type: cross Abstract: Predicting microsatellite instability (MSI) status from routine hematoxylin and eosin (H&E) whole slide images (WSIs) offers a practical alternative t
arXiv:2605.02462v1 Announce Type: cross Abstract: We study the problem of black-box optimization of a function f of any dimension, given function evaluations perturbed by noise. The function is assume
Autonomous software development startup Blitzy Inc. said today it has raised 200 million in new funding on a valuation of 1.4 billion to expand its enterprise coding platform. The company was founded
arXiv:2605.02745v1 Announce Type: new Abstract: Molecular property models increasingly support high-stakes drug-discovery decisions, but their outputs are often difficult to audit: classical predictor
Meta is facing a class action lawsuit filed by five major book publishers and one author over claims the company 'engaged in one of the most massive infringements of copyrighted materials in history'
arXiv:2401.16764v5 Announce Type: replace Abstract: Witnessing the evolution of text-to-image diffusion models, significant strides have been made in text-to-3D generation. Currently, two primary para
arXiv:2311.10320v3 Announce Type: replace Abstract: Data collected by different modalities can provide a wealth of complementary information, such as hyperspectral image (HSI) to offer rich spectral-s