Knowledge catalogue
arXiv:2609.22231v1 Announce Type: new Abstract: Long-horizon interactions with LLM-based assistants require memory systems that preserve and update user states, preferences, and interaction histories.
arXiv:2609.22171v1 Announce Type: new Abstract: Precision healthcare, particularly for conditions like hypertension and cardiovascular disease, necessitates monitoring of dietary sodium intake. Howeve
arXiv:2609.24246v1 Announce Type: new Abstract: Large language models (LLMs) have shown remarkable progress in natural language understanding, yet their effectiveness in specialized fields like astron
arXiv:2609.22246v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to forecast real-world events by retrieving and reasoning over news. We show that this dependence on
arXiv:2609.23971v1 Announce Type: cross Abstract: Two transformative classes of AI systems are reshaping how organizations operate: extit{digital AI}, which reasons over enterprise knowledge to power
arXiv:2609.21863v1 Announce Type: new Abstract: Empirical evaluation is central to recommender-systems (RecSys) research, but turning experimental designs into executable code remains a manual and err
Hey everyone, I wanted to share a project I’ve been working on called Jayce. The whole thing started because I was watching a toddler named learn the names of stuff He didn't need to completely rewire
I've been building an open-source AI workflow automation platform for a while now, mostly as a solo project. I recently checked the telemetry dashboard and was honestly surprised to see 1,062 telemetr
You can now automate EDD (eval-driven development) with Coding Harness Agents > build a baseline LLM-based application > score every change with judge evals > keep what improves, reject what regresses
arXiv:2609.19180v1 Announce Type: new Abstract: Language models face unique challenges in analyzing interdisciplinary scientific research literature. In biophysics research, faithful answers require g
arXiv:2609.19569v1 Announce Type: cross Abstract: Disease severity classification for genetic conditions is subjective and labor-intensive, creating bottlenecks in genomic screening, where commercial
This week we kicked off the DevFest season in North America at Google Hudson Square in New York City with 80 engineers packed into the room. Typical technical workshops hand you a finished repo, tell
arXiv:2609.19897v1 Announce Type: new Abstract: Historical archives pose a difficult retrieval problem for retrievalaugmented generation systems: documents are OCR-degraded, heterogeneous across genre
arXiv:2609.18182v1 Announce Type: new Abstract: Real-world agents fundamentally require persistent non-parametric knowledge for dynamic reasoning, i.e., long-term memory and retrieval-augmented genera
arXiv:2609.17247v1 Announce Type: new Abstract: An agentic AI driver-assistance framework that integrates perception, compliance reasoning, vehicle-state interpretation, and safety arbitration into a
arXiv:2609.17081v1 Announce Type: new Abstract: Grounded language-model systems are often evaluated by final answer accuracy, yet a correct answer can be unsupported, drawn from the wrong source, or p
arXiv:2609.16155v1 Announce Type: cross Abstract: This paper presents a novel framework leveraging Large Language Models (LLMs) to generate synthetic time series data for manufacturing processes. Moti
As enterprise organizations scale mission-critical applications, storage I/O and memory access can become severe operational bottlenecks. Whether its Oracle databases, in-memory databases like SAP HAN
arXiv:2609.16984v1 Announce Type: new Abstract: Open-weight language models publish the strings their chat templates use to mark turns, roles and tool results, which the tokenizer maps back to the res
arXiv:2609.16189v1 Announce Type: new Abstract: Open-ended strategic wargames are high-stakes LM-based social simulations: they model adversaries, institutions, escalation, plan brittleness, doctrine,
arXiv:2609.16847v1 Announce Type: cross Abstract: Region-level retrieval aims to align user-specified image regions with relevant regions or textual descriptions, playing a crucial role in realworld a
arXiv:2609.17346v1 Announce Type: cross Abstract: To answer questions outside of their pre-training data, large language models (LLMs) need access to new information, which can be presented in the con
arXiv:2609.14739v1 Announce Type: cross Abstract: Large language models are increasingly used in high-stakes domains such as law, where systems must ground their reasoning in retrieved evidence and ab
arXiv:2609.13860v1 Announce Type: new Abstract: Querying clinical trial registries remains a manual and error-prone process, requiring researchers to navigate large volumes of semi-structured data wit
arXiv:2508.02312v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs), now a foundation in advancing natural language processing, power applications such as text generation, machine t
arXiv:2609.13670v1 Announce Type: new Abstract: Event linking associates event mentions in text with entries in a knowledge base (KB), or identifies them as out-of-KB events. Although existing methods
arXiv:2609.13692v1 Announce Type: cross Abstract: LLM serving reuses KV cache by exact prefix match, so when a prompt is assembled from a set of reusable pieces -- retrieved passages, tool definitions
arXiv:2609.14412v1 Announce Type: new Abstract: Deep research agents answer complex questions through iterative loops of searching, reading, and reasoning. Recent work on reasoning-intensive benchmark
arXiv:2609.14245v1 Announce Type: cross Abstract: Context compression reduces generator input in retrieval-augmented generation, but answer quality alone does not characterize citation attribution. We
The LA Agentic AI Meetup in on the Tech Week calendar. Join us Tuesday, October 13, 5 to 7pm at Gulp in Playa Vista, for a few live demos, drinks, and real people comparing notes on what they're build
arXiv:2609.15309v1 Announce Type: new Abstract: Large language model (LLM) agents allocate test-time compute adaptively as they revise solutions, use tools, explore alternatives, and decide when to st
arXiv:2606.23189v2 Announce Type: replace-cross Abstract: Computer-use agents (CUAs) now act on a user's behalf across personal applications such as email, calendars, and to-do lists. This cross-appli
arXiv:2609.12686v1 Announce Type: cross Abstract: Large language models (LLMs) process long contexts, including long documents and lengthy conversations, but face token-level memory usage that increas
This is all I will say on the matter: It’s alarming to see the constant effort to try to tell me how I should use AI, how I should build AI, and now how I should pace it. Is it just me, or are all the
arXiv:2609.10964v1 Announce Type: new Abstract: Agentic LLM workflows consist of sequences of model turns interleaved with tool interactions, so their end-to-end completion time depends not only on in
arXiv:2609.11493v1 Announce Type: new Abstract: Chemistry, Manufacturing and Controls (CMC) process development generates an enormous body of technical information across a multi-stage, knowledge-inte
arXiv:2609.10817v1 Announce Type: cross Abstract: How does cooperation evolve in complex agentic systems? Prior work in evolutionary game theory studies why individuals are incentivized to cooperate b
arXiv:2609.11569v1 Announce Type: cross Abstract: We present EXYGEN (EXplore Your Graphs ENgine), a framework for knowledge graph (KG) understanding that enables conversational access to KGs at scale.
arXiv:2609.11673v1 Announce Type: new Abstract: Automated plankton imaging produces severely long-tailed datasets, where the rare taxa of greatest ecological interest have too few images to train or e
arXiv:2609.09242v1 Announce Type: cross Abstract: Large Language Models (LLMs) often generate natural-language comments while writing code, and these comments become part of the context used to genera
arXiv:2609.09503v1 Announce Type: new Abstract: Rapid bespoke commissioning of the Cognitive Digital Twin (CDT) is a major challenge in reconfigurable manufacturing. Traditional digital twin (DT) cons
arXiv:2609.08566v1 Announce Type: new Abstract: KV cache is evolving from a serving optimization into an external memory substrate for long-term LLM agents. In a shared multi-user deployment, however,
arXiv:2609.08173v1 Announce Type: new Abstract: Sparse autoencoder (SAE)-based steering has been widely used to address knowledge conflicts by guiding LLMs to be more faithful to the contextual knowle
arXiv:2609.07262v1 Announce Type: cross Abstract: Late-interaction visual document retrievers preserve fine-grained page evidence by storing many token embeddings per page, but the resulting storage a
arXiv:2609.06128v1 Announce Type: new Abstract: Production LLM agents execute tool-calling loops, retrieval chains, and compositional workflows in multiple modes, yet execution semantics are often cou
arXiv:2609.09684v1 Announce Type: new Abstract: Medical question-answering datasets often contain answer labels, whereas high-quality rationales remain scarce, noisy, or costly to validate. This chang
arXiv:2609.08686v1 Announce Type: new Abstract: Long-form instructional videos require automatic chaptering to support browsing, navigation, and knowledge access. Recent long-context language models c
arXiv:2609.09025v1 Announce Type: new Abstract: State-of-the-art vision models process images in their entirety, lacking the ability to selectively zoom in on relevant regions. This limitation is part
We’ve been building PipesHub for a while now, and I’d love to get more teams to try it and tell us where it breaks. The problem we kept running into was pretty simple: Building an AI app over company
Executive Summary Since the release of our May 2026 report detailing adversarial misuse of artificial intelligence (AI), Google Threat Intelligence Group (GTIG) has observed forward leaning adversarie
arXiv:2609.04598v1 Announce Type: cross Abstract: We introduce PetQA, a Korean long-form question-answering (QA) benchmark for evaluating veterinary knowledge and clinical reasoning in large language
Been posting individual pieces of RunAnywhere for months. Here's the whole thing in one place. RunAnywhere SDKs is a complete inference suite for any dev who wants to run AI on the user's device. ->8
Hi, I am thinking about putting some money / time into my local ai learning path and 'cleared' my attic where I found the following hardware. 3 x NUC11 (Core i5 1145G7 / 2,6 GHz, 64 GB RAM DDR4 2666MH
NVIDIA NemoClaw delivers a memory‑driven Chief of Staff agent that constructs a structured self‑model (people, projects, priorities) stored in Markdown pages, with an SQLite ledger recording obligatio
arXiv:2609.03209v1 Announce Type: new Abstract: We study a governed approach to enterprise analytics: a language model interprets the question, while deterministic policy selects and runs a pre-approv
arXiv:2508.00669v2 Announce Type: replace-cross Abstract: The proliferation of Large Language Models (LLMs) in medicine has enabled impressive capabilities, yet a critical gap remains in their ability
arXiv:2406.16893v3 Announce Type: replace-cross Abstract: The emergence of Transformer-based Large Language Models (LLMs) has substantially augmented the capabilities of Natural Language Processing (N
arXiv:2507.21815v2 Announce Type: replace Abstract: Millions of individuals' well-being are challenged by the harms of substance use. Harm reduction as a public health strategy provides non-judgementa
arXiv:2609.01618v1 Announce Type: cross Abstract: Telecom Service and Network Operations Centers (SNOCs) rely on large collections of cloud documents, including Standard Operating Procedures (SOPs), v
arXiv:2609.02366v1 Announce Type: cross Abstract: Named Entity Recognition (NER) has achieved substantial progress since the advent of large language models (LLMs). Nevertheless, the recognition of lo