Knowledge catalogue
This post likely discusses Sam Altman's observation of a large language model (LLM) demonstrating GUI operation at human-comparable speeds, highlighting a notable advancement in AI capability for inte
arXiv:2604.14116v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have empowered AI research agents to perform isolated scientific tasks, automating complex, real-world workflows, s
arXiv:2604.12543v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to translate the technical outputs of eXplainable Artificial Intelligence (XAI) methods into accessib
Speculative decoding is a technique used to accelerate the slow, sequential token generation (decode stage) in LLM inference. This method significantly reduces latency and improves hardware utilizatio
arXiv:2604.12545v1 Announce Type: new Abstract: Improving policymaking is a central concern in public administration. Prior human subject studies reveal substantial cross-cultural differences in citiz
arXiv:2604.12948v1 Announce Type: new Abstract: LLM agents with persistent memory store information as flat factual records, providing little context for temporal reasoning, change tracking, or cross-
arXiv:2603.27306v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have been proposed as supervisory agents for spacecraft operations, but existing approaches rely on static prompt
arXiv:2604.12721v1 Announce Type: new Abstract: Clinical case formulation organizes patient symptoms and psychosocial factors into causal models, often using the 5P framework. However, constructing su
arXiv:2604.12218v1 Announce Type: new Abstract: System log anomaly detection is critical for maintaining the reliability of large-scale software systems, yet traditional methods struggle with the hete
arXiv:2604.12601v1 Announce Type: cross Abstract: Passwords still remain a dominant authentication method, yet their security is routinely subverted by predictable user choices and large-scale credent
IBM Research has demonstrated that mid-training — a dedicated training phase between initial pre-training and fine-tuning — is essential for improving reasoning capabilities in large language models (
arXiv:2604.00136v2 Announce Type: replace-cross Abstract: Multi-model LLM serving operates in a non-stationary, noisy environment: providers revise pricing, model quality can shift or regress without
arXiv:2604.12177v1 Announce Type: new Abstract: LLM-based agents can execute actions that are syntactically valid, user-sanctioned, and semantically appropriate, yet still violate organizational polic
@pumfleet @calcom Did you see this piece by @dbreunig? He argues that the cost of locking down software through LLM analysis makes open source MORE valuable now: https://www.dbreunig.com/2026/04/14/cy
The most powerful LLM to run at home: 소형 로컬LLM 중 가장 강력한 모델을 소개합니다. 🔥SuperGemma4-31b-abliterated 우리가 원하는 로컬 모델의 모든것 - 무검열, 가벼움, 똑똑함 벤치마크 평가 : MMLU, GPQA, IFEval 등 벤치 항목을 종합하여 판단. 모델의 태생 약점, 비효율적인 연산단계와
arXiv:2604.10547v1 Announce Type: new Abstract: We introduce Agent^2 RL-Bench, a benchmark for evaluating agentic RL post-training -- whether LLM agents can autonomously design, implement, and run com
arXiv:2604.10352v1 Announce Type: new Abstract: Stateful tool-using LLM agents treat the context window as working memory, yet today's agent harnesses manage residency and durability as best-effort, c
Konstantin Kakaes / Quanta Magazine: How some mathematicians are exploring ways to incorporate LLM models into their research without losing direct experience with mathematical understanding — Those c
arXiv:2604.09601v1 Announce Type: new Abstract: Discovering predictive alpha factors in quantitative finance remains a formidable challenge due to the vast combinatorial search space and inherently lo
arXiv:2604.09566v1 Announce Type: cross Abstract: The application of games as a therapeutic tool for cognitive training is beneficial for patients with cognitive impairments. However, effective game d
arXiv:2604.09620v1 Announce Type: cross Abstract: Large language models are increasingly used to support organizational decisions from hiring to governance, raising fairness concerns in AI-assisted ev
arXiv:2604.10633v1 Announce Type: new Abstract: LLM-based universal information extraction (UIE) methods often rely on additional information beyond the original training data, which increases trainin
arXiv:2604.10842v1 Announce Type: cross Abstract: LLM-powered coding agents increasingly rely on tool-use protocols such as the Model Context Protocol~(MCP) to read and write files on a developer's wo
arXiv:2604.11080v1 Announce Type: cross Abstract: Rotation-based Post-Training Quantization (PTQ) has emerged as a promising solution for mitigating activation outliers in the quantization of Large La
arXiv:2603.14968v2 Announce Type: replace-cross Abstract: While watermarking serves as a critical mechanism for LLM provenance, existing secret-key schemes tightly couple detection with injection, req
arXiv:2604.11610v1 Announce Type: new Abstract: As LLM-based assistants become persistent and personalized, they must extract and retain useful information from past conversations as memory. However,
arXiv:2509.23808v4 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) for LLM reasoning is often framed as balancing exploration and exploitation in action sp
arXiv:2604.05549v2 Announce Type: replace Abstract: With the widespread application of LLM-based agents across various domains, their complexity has introduced new security threats. Existing red-team
arXiv:2604.11557v1 Announce Type: new Abstract: Tool-use capability is a fundamental component of LLM agents, enabling them to interact with external systems through structured function calls. However
arXiv:2601.17172v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly capable of generating personalized, persuasive text at scale, raising new questions about bias a
arXiv:2604.10101v1 Announce Type: new Abstract: The rapid development of large language models (LLMs) has extended text generation tasks into the literary domain. However, AI-generated literary creati
arXiv:2604.08931v1 Announce Type: new Abstract: Human cognitive development is shaped not only by individual effort but by structured social interaction, where role-based exchanges such as those betwe
arXiv:2601.18150v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) for large language models (LLMs) is increasingly bottlenecked by rollout (generation), where long output sequence
This r/ollama Reddit post discusses the combined use of a locally running LLM via Ollama alongside cloud-based AI APIs, exploring how users can leverage both approaches within the same workflow. The d
🚨 SUPER GEMMA 4 26B UNCENSORED IS INSANE LLM WIZARD COOKING AGAIN @songjunkr Dropped SuperGemma4-26B-Uncensored GGUF v2 and it’s trending on @huggingface🤗 This thing SMOKES the regular Gemma-4 26B: 🤯0
arXiv:2604.09034v1 Announce Type: new Abstract: The rapid evolution of Large Language Models (LLMs) has significantly impacted the field of natural language processing, but their growing complexity ra
arXiv:2604.09048v1 Announce Type: cross Abstract: While the large energy consumption of Large Language Models (LLMs) is recognized by the community, system operators lack guidance for energy-efficient
A developer shared a self-built local LLM client on the r/ollama subreddit, distinguishing it from the many existing options by emphasizing a polished, well-designed user interface and a complete abse
A Reddit post on r/ChatGPT in which the author shares their findings after a year of testing and comparing LLM subscription services across different price tiers (e.g., 20/month, higher-cost tiers). T
Neat experiment finds AI fact checks are rated as more helpful & less ideological than human ones 'LLM-generated Community Notes can achieve broader cross-ideological acceptance than human-written not
This post is so so good. We are at this interesting point where we’ve started to really figure out ‘memory’ with these LLM-based systems. And @hwchase17 is totally right - memory is basically just con
arXiv:2410.22177v2 Announce Type: replace-cross Abstract: As more applications of large language models (LLMs) for 3D content for immersive environments emerge, it is crucial to study user behaviour t
arXiv:2506.06975v5 Announce Type: replace-cross Abstract: As API access becomes a primary interface to large language models (LLMs), users often interact with black-box systems that offer little trans
arXiv:2510.18196v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are commonly used as evaluators in various applications, but the reliability of the outcomes remains a challenge.
arXiv:2604.08075v1 Announce Type: new Abstract: Production vLLM fleets typically provision each instance for the worst-case context length, leading to substantial KV-cache over-allocation and under-ut
arXiv:2604.06297v1 Announce Type: cross Abstract: Given the growing reliance on private data in training Large Language Models (LLMs), Federated Learning (FL) combined with Parameter-Efficient Fine-Tu
arXiv:2604.06664v1 Announce Type: cross Abstract: Modern LLM service providers increasingly rely on autoscaling and parallelism reconfiguration to respond to rapidly changing workloads, but cold-start
Indeed, if the LLM crew would just stick to this narrative, I would have a *lot* less to say 🤷♂️ @GaryMarcus All we want is truth. Instead of overhyping LLMs, they should keep narative: -LLMs are use
LiteParse is the best document parsing library for coding agents. It's free, fast, integrates natively with the LLM's native visual understanding capabilities, and comes with support for 50+ formats a
arXiv:2510.13907v3 Announce Type: replace Abstract: Large language models (LLMs) are highly sensitive to prompts, but most automatic prompt optimization (APO) methods assume access to ground-truth ref
arXiv:2508.20340v4 Announce Type: replace-cross Abstract: Satisfiability Modulo Theory (SMT) solvers are foundational to modern systems and programming languages research, providing the foundation for
Pills for llm coding from an OpenAI talk at @aiDotEngineer : - have single shared utils to do stuff like bounded concurrency - treat errors as values and part of the control flow - use telemetry for e
arXiv:2604.06401v1 Announce Type: new Abstract: The large language models (LLMs) might produce a persuasive argument within mathematical and logical fields, although such argument often includes some
arXiv:2512.01925v2 Announce Type: replace-cross Abstract: Recent advancements in large language models (LLMs) have been driven by their emergent reasoning capabilities, particularly through long chain
The search did not return the specific Reddit post. Based on available context from the search results and the post title itself, I cannot accurately summarize the Reddit thread's content without r...
arXiv:2603.11394v2 Announce Type: replace Abstract: Patients and clinicians are increasingly using chatbots powered by large language models (LLMs) for healthcare inquiries. While state-of-the-art LLM
The ‘agent harness’ is essentially the new runtime. It’s like a lightweight OS around an LLM—handling memory, tool calls, retries, and control flow. @hwchase17 im excited about agent harnesses because
I think the story that was shared in the Mythos System Card still has the signs of flawed LLM writing (which looks like good writing at first glance): A story that doesn't really hold together logical
arXiv:2610.20634v1 Announce Type: new Abstract: Retrieval-augmented generation asks one question at volume: does this evidence support this claim? The answer is one bit, yet most pipelines obtain it f
arXiv:2610.21412v1 Announce Type: new Abstract: Large language model (LLM) agents now fix software, operate computers and serve customers, but their harnesses, the programs that run them, call a large