Knowledge catalogue
arXiv:2608.19026v1 Announce Type: new Abstract: Released in 2025, Institutional Books: Harvard Library (IB-HL) is a collection of 983,004 volumes (242B o200k_base tokens), originally digitized through
arXiv:2608.18972v1 Announce Type: new Abstract: Historical newspapers are an abundant record of public life, but their dense, irregular and sometimes noisy layouts make computational access to these m
I have a big database of local court decisions with a legal sentence which is like a paragraph summary of the doc. I've been tinkering with FTing for many days now, all results inconclusive never beat
arXiv:2608.18082v1 Announce Type: new Abstract: Although context windows have expanded significantly in recent years, hallucinations in long-context summarization remain a challenge. Long novels are b
arXiv:2608.18744v1 Announce Type: new Abstract: Agents improve quickly against a reliable automatic metric and stall without one, and the applications that need them most, report generation among them
arXiv:2608.18716v1 Announce Type: new Abstract: Diagnosing faults in rotating machinery is essential for ensuring the reliability of industrial processes. Random convolutional kernel-based Time Series
oooooh fancy new site? @shubhamintech Stop using your agent logs just for debugging. Use them to train your own model. Today we're launching Agnost AI (YC S26)'s first model: agnost-*******-0.1 Traine
arXiv:2608.18516v1 Announce Type: cross Abstract: Precise segmentation of the optic disc and cup is critical for the early detection and diagnosis of glaucoma. However, achieving consistently high per
arXiv:2608.18846v1 Announce Type: new Abstract: Last-mile delivery aims to handle dynamically arriving orders with couriers while modeling complex spatial and temporal correlations. Recent learning-ba
https://reddit.com/link/1vtkgdj/video/595yn0ckdjkh1/player I wanted to try out Qwen3.8 27B 's SVG capabilities but with something different than the pelican on a bicycle. Promt was literally just : cr
arXiv:2608.18165v1 Announce Type: new Abstract: Knowledge graphs modeled in RDF are powerful for describing static knowledge, but they cannot capture or reason about the dynamic behavior of physical s
arXiv:2608.18410v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models process long multimodal token sequences, making inference expensive in both memory and computation. Existing efficie
arXiv:2608.18864v1 Announce Type: new Abstract: LiDAR scene flow estimates point-wise motion between two consecutive scans, referred to as the source and target. Leading self-supervised methods typica
arXiv:2608.18779v1 Announce Type: cross Abstract: Semantic-ID mappings are reusable interfaces between item tokenizers and generative recommenders, yet released mappings rarely state whether they are
this screenshot is without MTP usage , fully offloaded onto the GPU. using LM STUDIO i wanted to ask you guys if theres a way to make it even faster , as MTP really didnt help and is infact slower due
arXiv:2608.19197v1 Announce Type: cross Abstract: Continuous self-improvement requires an ever-expanding pool of self-generated, diverse, adaptive goals. For language agents, existing training environ
They released both GGUFs & custom llama.cpp fork today. 35B MOE in 7GB size which's good for Mobile & Edge devices(Also low memory systems). Up to 120 t/s on Consumer Laptop. GGUFs: https://huggingfac
arXiv:2608.18931v1 Announce Type: cross Abstract: Test-time scaling (TTS) improves language model outputs by spending additional inference compute - generating multiple candidates, searching over part
this is going to expose a lot of bad products Stop using your agent logs just for debugging. Use them to train your own model. Today we're launching Agnost AI (YC S26)'s first model: agnost-*******-0.
arXiv:2608.18500v1 Announce Type: new Abstract: Tropical cyclones (TCs) pose severe risks from strong winds and heavy rainfall. However, forecasting their track and intensity remains challenging due t
arXiv:2608.18158v1 Announce Type: cross Abstract: LLMs have been increasingly used to catch data quality issues automatically, but we know very little about how consistent these judgments actually are
Adronite Inc. today launched Codistry, an artificial intelligence coding platform for large enterprise codebases. The platform runs on Adronite’s Context Engine, or ACE, which the company has patented
arXiv:2608.17923v1 Announce Type: new Abstract: Appendicitis is one of the most common abdominal emergencies worldwide and requires prompt diagnosis and treatment to prevent life-threatening condition
arXiv:2608.17856v1 Announce Type: new Abstract: Tabular prediction is a critical task across numerous applications. The recent success of large language models has sparked various approaches for adapt
arXiv:2608.17995v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) achieve high-quality generation but are costly due to iterative sampling. Dynamic-resolution sampling reduces early-stage
arXiv:2608.17291v1 Announce Type: new Abstract: Accurate 3D tooth segmentation forms the cornerstone of digital dentistry, yet it remains a formidable challenge due to the inherent intricacy of real-w
arXiv:2608.16919v1 Announce Type: cross Abstract: Recent advances in large language models and agent-based recommendation frameworks have introduced new opportunities for more flexible and context-awa
arXiv:2608.17884v1 Announce Type: new Abstract: Glioblastoma (GBM) is the most aggressive primary brain tumor in adults, with a median overall survival of 15 months. Longitudinal, multi-modal imaging
arXiv:2608.17550v1 Announce Type: cross Abstract: Academic papers are a primary carrier of scientific knowledge, yet most of this knowledge remains locked in PDFs that are optimized for human reading
arXiv:2608.17352v1 Announce Type: new Abstract: Distributed Denial-of-Service (DDoS) attacks threaten network availability, requiring a cognitive detection process that senses traffic, infers intent,
Couldn’t have said it better myself. AI is excellent at discovering things which are already very well understood somewhere else. How Anthropic's new results post would read without the PR: Claude orc
OpenAI Group PBC recently paused some of its artificial intelligence training workloads over concerns that they could cause cybersecurity issues. The ChatGPT developer disclosed the move in a blog pos
arXiv:2608.17776v1 Announce Type: new Abstract: We demonstrate that RL finetuning an LLM using debate, a two-player adversarial game between a generator and a critic adjudicated by a weaker LLM judge,
llama.cpp pr #27342 adds dflash2, so i rented an rtx 6000 and ran the same four prompts through four decoding setups on qwen3.8 27B median results over the four tasks: baseline 47.4 tok/s mtp 114.7 to
arXiv:2608.17069v1 Announce Type: cross Abstract: Federated deployments of variational quantum classifiers are attractive for cross-organisation risk prediction in supply chains, because raw data neve
arXiv:2608.17941v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) improves the reasoning capabilities of large language models but relies on costly rollout explor
arXiv:2608.17524v1 Announce Type: new Abstract: This preliminary paper outlines a planned evaluation benchmark for Explainable Reinforcement Learning (XRL) methods. Current evaluations rely on functio
arXiv:2607.15209v2 Announce Type: replace Abstract: Multilingual pre-trained language models such as XLM-R perform well for major languages but struggle with low-resource Ge'ez-script languages, large
arXiv:2509.12040v3 Announce Type: replace-cross Abstract: Open-Vocabulary Remote Sensing Image Segmentation (OVRSIS), an emerging task that adapts Open-Vocabulary Segmentation (OVS) to the remote sens
arXiv:2608.17203v1 Announce Type: cross Abstract: Contrastive learning has become a cornerstone of modern representation learning, powering CLIP-style models that underpin text-to-image generation, vi
arXiv:2607.16660v2 Announce Type: replace-cross Abstract: The increasing adoption of Large Language Models (LLMs) as AI components in modern software systems introduces distinct security risks to the
arXiv:2608.01324v2 Announce Type: replace Abstract: Deep search has become a fundamental capability of large language models (LLMs) for solving open-domain complex tasks. However, existing approaches
arXiv:2502.00213v5 Announce Type: replace-cross Abstract: Transformers are difficult to optimize with stochastic gradient descent (SGD) and largely rely on adaptive optimizers such as Adam. Despite ex
arXiv:2608.16890v1 Announce Type: new Abstract: Clinical trial programming -- transforming study protocols into analysis-ready datasets under CDISC standards -- is a bottleneck in regulatory submissio
arXiv:2508.06692v3 Announce Type: replace Abstract: Federated learning systems typically allocate gradient compression by link speed. This is sensible when bandwidth and data informativeness align. Ho
arXiv:2312.06576v2 Announce Type: replace Abstract: Graph Transformers (GTs) facilitate the comprehension of complex relationships on graph-structured data by leveraging self-attention of the possible
.@Kimi_Moonshot Kimi K3 is starting to roll out on Ollama's cloud subscriptions. We are working on improving Ollama's cloud to be much more transparent on the pricing to show the best performance / $.
arXiv:2608.17836v1 Announce Type: new Abstract: As large language models (LLMs) are granted increasing autonomy, it is essential to investigate methods that can induce unsafe behavior. We propose a no
arXiv:2608.17330v1 Announce Type: new Abstract: Large language models for medical consultation are often evaluated after a clinical problem has already been made clear, although real consultations may
arXiv:2409.14644v4 Announce Type: replace-cross Abstract: The advent of large language models (LLMs) has significantly advanced artificial intelligence in software engineering, with source code embedd
arXiv:2608.16975v1 Announce Type: new Abstract: With the rapid advancement of large language models, brain-language decoding has achieved remarkable progress. However, it remains unclear whether decod
arXiv:2608.17244v1 Announce Type: cross Abstract: This paper addresses the limitations of Gaussian distribution assumptions in statistical sparse learning, particularly in modeling correlated and hete
arXiv:2506.01297v5 Announce Type: replace Abstract: Representation learning of geospatial locations remains a core challenge in achieving general geospatial intelligence, with increasingly diverging p
More open weights frontier for generative media, more... impossible to not think of @c_valenzuelab's excellent blog 'we are solving graphics backwards' in it, he argues that in traditional computer gr
OpenAI Group PBC is falling further behind its rival Anthropic PBC, if its latest financials are any indication. The artificial intelligence model maker told investors that its revenue rose 18% on a s
arXiv:2608.18035v1 Announce Type: new Abstract: Traffic elements such as traffic lights and road signs play a fundamental role in human driving decisions and should naturally influence end-to-end driv
arXiv:2608.17173v1 Announce Type: cross Abstract: Online decision making often requires navigating a landscape shaped by both dynamic contexts and strategic interactions. In competitive pricing, for e
arXiv:2608.17781v1 Announce Type: new Abstract: ML systems increasingly condition decisions on downstream model identity, but this is useful only if model-specific differences form reusable structure
arXiv:2608.17966v1 Announce Type: new Abstract: Sparse attention mechanisms, which score all token pairs but propagate only the strongest, now underpin the most efficient Transformers for lightweight
arXiv:2608.17007v1 Announce Type: new Abstract: Agent Skills can specify procedural and resource obligations for tool use, and language models instantiate them as concrete programs. However, when mode