Knowledge catalogue
arXiv:2608.15888v1 Announce Type: new Abstract: LLM-based agents can act on behalf of a user to access cloud services, call tools, or invoke agents. At session start, the agent's permissions are set b
DFlash 2 is here! Qwen3.8-27B at 70 tok/s on an M5 Max MacBook Pro. ⚡ Up to 4.6× the speed of autoregressive decoding, with the same output. This is the next generation of DFlash, seeded at Z Lab and
arXiv:2608.14644v1 Announce Type: cross Abstract: Real-world LLM deployments increasingly rely on runtime-injected prohibitions--enterprise policies, PII redlines, tool boundaries--that vary per reque
arXiv:2608.15163v1 Announce Type: new Abstract: Visual brain decoding reconstructs visual content perceived by a person from neural measurements such as fMRI, providing a computational approach to stu
arXiv:2608.15703v1 Announce Type: new Abstract: Large language model (LLM) agents often perform poorly on complex, long-horizon tasks because their context becomes increasingly cluttered over time. As
Hey everyone, I am trying to make a LLM interface optimized for AI-cowork experience. Heres what I've thought of and tried to fix: 1)You shouldn't have to copy and paste context for the AI model. 2)Yo
arXiv:2608.15579v1 Announce Type: cross Abstract: Industrial software-engineering teams increasingly need LLM agents that turn bug reports into correct patches, yet benchmark-scale operation adds long
arXiv:2603.24465v2 Announce Type: replace Abstract: Recent advances in large language models (LLMs) and LLM-based agents have substantially improved the capabilities of automated theorem proving. Howe
arXiv:2602.02414v2 Announce Type: replace Abstract: Timely and accurate identification of student misconceptions is key to improving learning outcomes and pre-empting the compounding of student errors
New benchmark categories for generative AI and agentic workflows arrive alongside updated LLM tests, as the industry standard for measuring PC AI performance evolves. The post MLPerf Client v2.0 Expan
arXiv:2608.15138v1 Announce Type: new Abstract: Designing an ABR algorithm for one network scenario takes an engineer months, and large language models now do this work in hours, matching or beating h
arXiv:2608.15834v1 Announce Type: new Abstract: Tool-calling LLM agents navigate unfamiliar codebases with a handful of generic primitives for listing, reading and searching files (ls, cat, grep). A k
arXiv:2608.16187v1 Announce Type: cross Abstract: AI-assisted development tools generate vulnerable code at significant rates, yet few automated mechanisms exist to detect, enrich, fix, and verify sec
arXiv:2608.16707v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as decision-making agents in settings that require sophisticated environmental exploration. How
arXiv:2608.14707v1 Announce Type: new Abstract: As large language model (LLM)-based multi-agent systems become increasingly capable, coordinating agents under uncertainty becomes a fundamental challen
arXiv:2608.15935v1 Announce Type: new Abstract: Jointly fine-tuning an LLM on meeting-summarisation corpora of widely varying size raises a question that prior work leaves confounded: when a domain-ba
arXiv:2608.16411v1 Announce Type: cross Abstract: LLM-based agents are rapidly moving from research prototypes into the core business processes of organizations, but these agents pose deployment risks
arXiv:2608.15193v1 Announce Type: cross Abstract: As large language model (LLM) agents are increasingly adopted in scientific research, external knowledge bases, knowledge graphs, and long-term memory
arXiv:2608.13900v1 Announce Type: cross Abstract: Large language model (LLM) agents are evolving from conversational assistants into autonomous systems that execute long-horizon tasks through reasonin
arXiv:2603.18871v2 Announce Type: replace Abstract: Urban Vehicular Ad-Hoc Networks (VANETs) can become fragmented because buildings obstruct wireless links and vehicle mobility continuously changes t
arXiv:2608.14303v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for code generation, yet they remain vulnerable to prompts that elicit insecure implementations. Exis
EXL3 is an alternative to llama.cpp. And while there is extensive tooling for llama.cpp, EXL3's primary deployment (TabbyAPI), has a OpenAI compatible API so it shouldn't matter. Why won't this tool m
arXiv:2608.13844v1 Announce Type: cross Abstract: Large language models (LLMs) have become core components of cloud-based intelligent services in academia and industry, yet their training and deployme
arXiv:2608.13863v1 Announce Type: new Abstract: Deep neural network (DNN) inference on mobile devices often incurs high latency and energy consumption due to limited computing and memory resources. To
arXiv:2604.06452v2 Announce Type: replace Abstract: When a colleague starts explaining something you already understand, you interrupt them. This simple act, a listener taking control of the conversat
arXiv:2608.14522v1 Announce Type: new Abstract: As AI systems make more morally loaded decisions across society, one response has been moral preference elicitation. In this approach, researchers poll
arXiv:2509.24148v4 Announce Type: replace-cross Abstract: Test-Driven Development (TDD) is a widely adopted practice that requires developers to create and execute tests alongside implementation. With
arXiv:2608.14426v1 Announce Type: new Abstract: AI is increasingly being used to help with AI R&D. Under certain conditions this feedback loop might be able to produce an intelligence explosion, with
one of my llm hobbies is re-creating graphics demos i used to write in BASIC in the late 1980s. i slopped together an agentic harness and a basic-to-js transpiler in a web page i've been playing with
I look to Simon for a broad survey of current LLM tech. Here's his review of playing with Qwen 3.8 27B. His comment on Mastodon was 'I can't remember the last time I've had this much fun playing with
Quick update on the RTX 5060 Ti local LLM repo. It has changed quite a bit since my previous posts. The project started as a collection of practical notes and benchmark results. That was useful, but a
So a bit of context, I am a cybersecurity senior analyst I am interested in LLMs for that field especially with MCPs to connect them to the tools or for writing scripts I started this field by doing a
arXiv:2608.12895v1 Announce Type: new Abstract: Compositional reliability bounds for multi-agent systems multiply component reliabilities, a step licensed by a conditional-independence assumption that
arXiv:2603.08322v2 Announce Type: replace Abstract: We study mathematical discovery through the lens of neurosymbolic reasoning, where an AI agent powered by a large language model (LLM), coupled with
arXiv:2608.12329v1 Announce Type: cross Abstract: Progress on AI for psychosis-risk assessment is limited by a data-access bottleneck. Real clinical interviews are difficult to share because of privac
arXiv:2608.12593v1 Announce Type: new Abstract: Discovery---formulating novel generalizations---is a central part of the scientific process. Despite its importance, there is a gap in the current AI be
Don't classify. Hallucinate! I still have quite a bit of older content on my blog that I never got round to tagging. My blog has 1,856 tags - likely too many to feed to an LLM in one go and say 'which
arXiv:2608.13063v1 Announce Type: new Abstract: Prior work on LLM behavior under anomalous conditions asks whether a model notices anomalies. We ask a narrower question: once a model sits in a workflo
arXiv:2601.10560v2 Announce Type: replace-cross Abstract: Multi-agent systems (MAS) coordinate multiple LLM-powered agents through structured workflows, gaining reasoning power but incurring high infe
arXiv:2608.13244v1 Announce Type: new Abstract: Local chemical perception and property reasoning are both essential for understanding how molecular structure determines properties. Current LLM-based c
arXiv:2412.17228v4 Announce Type: replace Abstract: Background: Clinical trials are essential to advancing cancer treatments, but fewer than 10% of adults with cancer enroll in therapeutic trials. Ope
arXiv:2608.13293v1 Announce Type: new Abstract: Edge AI deployment demands neural architectures that are simultaneously accurate, computationally efficient, and hardware-deployable - a challenge addre
arXiv:2608.12582v1 Announce Type: cross Abstract: AI journaling tools can tailor prompts to a person's own sensed behavior, but it is unclear which behaviors respond to them. We analyzed 369 journal e
arXiv:2608.12717v1 Announce Type: cross Abstract: Mechanistic interpretability of large language models lacks spatially resolved, falsifiable tools for testing whether internal components are speciali
arXiv:2512.19799v2 Announce Type: replace Abstract: Advances in LLM reasoning and tool use have enabled agentic science, yet frontier theoretical and computational physics remains challenging because
arXiv:2608.12395v1 Announce Type: new Abstract: We describe Research Assistant, an internal LLM-based system developed at AstraZeneca to help scientists and clinicians explore biomedical questions acr
arXiv:2608.13076v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable success in natural language understanding and generation, but their deployment is constrained by h
arXiv:2608.12654v1 Announce Type: new Abstract: Long-running LLM agents act through tools, and a single step can send an email, merge a pull request, or wire a payment. The steering decision is the pr
arXiv:2608.12336v1 Announce Type: cross Abstract: A story premise is the creative spark from which a full narrative can grow. Yet LLM-based story generation has mostly emphasized later-stage planning,
arXiv:2608.12751v1 Announce Type: cross Abstract: Logic synthesis transforms RTL designs into gate-level netlists, where PPA results are highly sensitive to the choice of optimization commands, making
arXiv:2608.12391v1 Announce Type: cross Abstract: Graph reasoning provides a promising testbed for evaluating the reasoning ability of large language models (LLMs), as graph instances can be programma
arXiv:2608.13263v1 Announce Type: new Abstract: Large language model serving faces a critical memory bottleneck: the KV cache grows with sequence length and batch size. PagedAttention uses fixed-size
Chinese artificial intelligence developer Z.ai Co. today debuted GLM-5.3, an open-source large language model that set records across several popular benchmarks. The LLM is based on an algorithm calle
arXiv:2608.11338v1 Announce Type: new Abstract: Recently, the practice of augmenting LLM agent capability with skills has gained prevalence. We explore the cost effective adaptation of agents to novel
arXiv:2604.03236v2 Announce Type: replace-cross Abstract: Large language model (LLM)-based educational assistants often provide direct answers offering little incentive for students to explore or enga
Computer History builds on the Chronicle research preview with reduced token usage and more privacy controls. A new timeline view gives you the ability to look back on your work and build skills from
arXiv:2608.11249v1 Announce Type: cross Abstract: We study the problem of lossless text compression, motivated by the rapid growth in the collection and storage of digital textual data - including pla
arXiv:2608.12133v1 Announce Type: new Abstract: Enterprise guideline documents are heterogeneous and multimodal, combining narrative text, complex tables, and embedded images. Existing LLM and VLM sys
arXiv:2608.11753v1 Announce Type: new Abstract: Financial text is produced and interpreted within a market environment, yet financial text classifiers almost always receive text alone. We study whethe
arXiv:2608.11361v1 Announce Type: cross Abstract: Tokenizer vocabulary size is a foundational design choice in large language model (LLM) infrastructure, yet it is typically fixed at training time bas