Search: “llm”

Instead of the gold standard, we can imagine an inference standard of exchange, the FLOP. (As opposed to tokens, this accounts for AI ability) With some AI help, I figure 1 buys roughly 10^17 managed-

arXiv:2604.12651v1 Announce Type: cross Abstract: Knowledge graph embedding (KGE) models perform well on link prediction but struggle with unseen entities, relations, and especially literals, limiting

arXiv:2604.12126v1 Announce Type: new Abstract: Large Language Models (LLMs) have significantly advanced tool-augmented agents, enabling autonomous reasoning via API interactions. However, executing m

arXiv:2604.11868v1 Announce Type: new Abstract: While medical Vision-Language models (VLMs) achieve strong performance on tasks such as tumor or organ segmentation and diagnosis prediction, their opaq

arXiv:2604.12955v1 Announce Type: new Abstract: There is growing interest in leveraging large language models (LLMs) for text-to-model translation and optimization tasks. This paper aims to advance th

arXiv:2604.12766v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) typically relies on a flat retrieval paradigm that maps queries directly to static, isolated text segments. This ap

arXiv:2604.11862v1 Announce Type: cross Abstract: In optimization problems, some variable subsets may have a joint non-linear or non-monotonical influence on the function value. Therefore, knowledge o

arXiv:2502.11271v2 Announce Type: replace-cross Abstract: Solving complex reasoning tasks may involve visual understanding, domain knowledge retrieval, numerical calculation, and multi-step reasoning.

This Reddit post likely showcases a custom or community-built dashboard designed to provide comprehensive observability for OpenAI agents, covering real-time monitoring of agent activity, memory state

John Collison / Cheeky Pint: Q&A with ElevenLabs co-founder Mati Staniszewski on how audio models work, the company's business model, the conversational Turing Test, voice agents, and more — Mati Stan

I think we will see some people employed (though perhaps not explicitly) as meat shields: people who are accountable for ML systems under their supervision. The accountability may be purely internal,

arXiv:2604.12582v1 Announce Type: new Abstract: Recent Video Large Language Models (Video-LLMs) have demonstrated strong capability in video understanding, yet they still suffer from hallucinations. E

arXiv:2512.14754v2 Announce Type: replace-cross Abstract: Advanced LLMs have achieved near-ceiling instruction-following accuracy on benchmarks such as IFEval. However, these impressive scores do not

arXiv:2604.12988v1 Announce Type: cross Abstract: Execution Accuracy (EX), the widely used metric for evaluating the effectiveness of Natural Language to SQL (NL2SQL) solutions, is becoming increasing

arXiv:2604.12377v1 Announce Type: cross Abstract: Korean is a morphologically rich language with a featural writing system in which each character is systematically composed of subcharacter units know

arXiv:2505.18646v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated effectiveness in code generation tasks. To enable LLMs to address more complex coding challenge

arXiv:2604.12040v1 Announce Type: cross Abstract: We present SIR-Bench, a benchmark of 794 test cases for evaluating autonomous security incident response agents that distinguishes genuine forensic in

arXiv:2506.14512v4 Announce Type: replace Abstract: Large Language Models (LLMs) have undergone rapid progress, largely attributed to reinforcement learning on complex reasoning tasks. In contrast, wh

Written by: Jamie Collier, Robin Grunewald Germany has reclaimed its position as a primary focus for cyber extortion in Europe. While data leak site (DLS) posts rose almost 50% globally in 2025, Googl

arXiv:2604.12046v1 Announce Type: new Abstract: Large language models (LLMs) often hallucinate in long-form generation. Existing approaches mainly improve factuality through post-hoc revision or reinf

Jerry Liu, co-founder of LlamaIndex, shared a post on X (formerly Twitter) expressing enthusiasm about a notable development, likely related to AI, large language models, or the LlamaIndex ecosystem.

arXiv:2509.07177v3 Announce Type: replace Abstract: Large language models have demonstrated impressive capabilities across various domains. However, their general-purpose nature often limits their eff

arXiv:2604.12321v1 Announce Type: new Abstract: Existing Chinese toxic content detection methods mainly target sentence-level classification but often fail to provide readable and contiguous toxic evi

arXiv:2604.12208v1 Announce Type: cross Abstract: Global navigation information and local scene understanding are two crucial components of autonomous driving systems. However, our experimental result

arXiv:2604.05818v2 Announce Type: replace-cross Abstract: Multi-modal Retrieval-Augmented Generation (RAG) has emerged as a highly effective paradigm for Knowledge-Based Visual Question Answering (KB-

arXiv:2604.10853v1 Announce Type: new Abstract: Task-oriented evaluation of knowledge graph (KG) quality increasingly asks whether an ontology-based representation can answer the competency questions

arXiv:2410.11964v2 Announce Type: replace Abstract: The log-linear model has received a significant amount of theoretical attention in previous decades and remains the fundamental tool used for learni

arXiv:2604.11791v1 Announce Type: cross Abstract: Reasoning has become a central capability in large language models. Recent research has shown that reasoning performance can be improved by looping an

arXiv:2604.10799v1 Announce Type: cross Abstract: The development of the Bielik v3 PL series, encompassing both the 7B and 11B parameter variants, represents a significant milestone in the field of la

arXiv:2601.04672v2 Announce Type: replace-cross Abstract: Agricultural disease diagnosis challenges VLMs, as conventional fine-tuning requires extensive labels, lacks interpretability, and generalizes

AI keeps getting better but the last time the shape of the jagged frontier changed radically was o1 & the Reasoner A good mental model of the coming months is that models get very good at the things t

arXiv:2604.10884v1 Announce Type: cross Abstract: Automated generation of executable Business Process Model and Notation (BPMN) models from natural-language specifications is increasingly enabled by l

// Artifacts as Memory Beyond the Agent Boundary // An agent doesn't always need a bigger memory buffer. Sometimes the environment itself remembers on the agent's behalf. New research formalizes this

arXiv:2604.09866v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have shown the promise to significantly accelerate the workflow by automating structural modeling and

arXiv:2603.27195v2 Announce Type: replace Abstract: Designing microstructures with coupled cross-physics objectives is a fundamental challenge where traditional topology optimization is often computat

arXiv:2604.11628v1 Announce Type: new Abstract: Existing conversational memory systems rely on complex hierarchical summarization or reinforcement learning to manage long-term dialogue history, yet re

arXiv:2604.11304v1 Announce Type: new Abstract: Existing AI benchmarks lack the fidelity to assess economically meaningful progress on professional workflows. To evaluate frontier AI agents in a high-

arXiv:2510.12460v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems often fail to maintain contextual faithfulness, generating responses that conflict with the provided co

arXiv:2604.10736v1 Announce Type: new Abstract: No open Irish-specific benchmark compares end-user ASR systems under a shared Irish-aware evaluation protocol. To solve this, we release BlasBench, an o

arXiv:2604.09691v1 Announce Type: cross Abstract: Educational diagrams -- labeled illustrations of biological processes, chemical structures, physical systems, and mathematical concepts -- are essenti

arXiv:2512.24503v2 Announce Type: replace-cross Abstract: Data teams at frontier AI companies routinely train small proxy models to make critical decisions about pretraining data recipes for full-scal

arXiv:2604.10825v1 Announce Type: new Abstract: We introduce CheeseBench, a benchmark that evaluates large language models (LLMs) on nine classical behavioral neuroscience paradigms (Morris water maze

arXiv:2601.14698v2 Announce Type: replace Abstract: Real-world fact-checking often involves verifying claims grounded in structured data at scale. Despite substantial progress in fact-verification ben

arXiv:2604.11801v1 Announce Type: new Abstract: With the recent progress of Large Language Models (LLMs), there is a growing interest in applying these models to solve complex and challenging problems

arXiv:2604.10235v1 Announce Type: new Abstract: Agentic code tasks such as fault localization and patch generation require processing long codebases under tight memory constraints, where the Key-Value

arXiv:2604.09836v1 Announce Type: new Abstract: AI agents hold growing promise for accelerating scientific discovery; yet, a lack of frontier evaluations hinders adoption into real workflows. Expert-w