Search: “llm”

arXiv:2509.23330v3 Announce Type: replace Abstract: Large language models (LLMs) have achieved significant advancements in reasoning capabilities through reinforcement learning (RL) via environmental

arXiv:2605.00536v1 Announce Type: cross Abstract: Scaling laws for Large Language Models (LLMs) establish that model quality improves with computational scale, yet edge deployment imposes strict const

arXiv:2605.00116v1 Announce Type: new Abstract: In this article, we introduce ViLegalNLI, the first large-scale Vietnamese Natural Language Inference (NLI) dataset specifically constructed for the leg

arXiv:2605.00796v1 Announce Type: cross Abstract: Background: Patient-facing medical chatbots based on retrieval-augmented generation (RAG) are increasingly promoted to deliver accessible, grounded he

arXiv:2602.13305v2 Announce Type: replace Abstract: Wildfires are a growing threat to ecosystems, human lives, and infrastructure, with their frequency and intensity rising due to climate change and h

An open-source locally-run conversational AI that moves beyond simple request-response models by implementing persistent memory, belief, and self-reflection. The system stores all user profiles, memor

JP Morgan's investment research team just shared exactly how they built their multi-agent system 'Ask David', and it's the same architecture pattern showing up everywhere: - supervisor agent orchestra

Automated lint: 45 errors, 11 warnings, 3 info

Of course Pynchon would call this correctly 40 years ago: “It will be amazing and unpredictable, and even the biggest of brass, let us devoutly hope, are going to be caught flat-footed.“ He and Dougla

Shame on the @AFpost for glorifying Dawkins’ foolish post without asking a single expert whether it made any sense whatsoever. Evolutionary biologist and outspoken atheist Richard Dawkins says that af

while exploring harnesses, i came across my first and favourite agent orchestration framework @LangChain has launched deep-agents last year. it’s a wonderful harness, that has a lot of tools: - write_

A lot of work around AI in 2023 was spent on building picks and shovels. I would know this because that was basically the core goal of the original @llama_index framework. Today, a lot of that is no l

People are really enjoying our full workshops showing end to end walkthroughs of real production workflows! This is a rare double header with @braintrust's Giran Moodley and @OussamaHaff walking thoug

arXiv:2604.27105v1 Announce Type: new Abstract: Analyzing mutual gaze (MG) and joint attention (JA) is critical in developmental psychology but traditionally relies on labor-intensive manual coding. A

arXiv:2604.27699v1 Announce Type: new Abstract: Current embodied agents are often limited to passive instruction-following or reactive need-satisfaction, lacking a stable, high-order value framework e

arXiv:2604.27251v1 Announce Type: cross Abstract: Large Language Models (LLMs) are known to acquire reasoning capabilities through shared inference patterns in pre-training data, which are further eli

arXiv:2602.24262v4 Announce Type: replace Abstract: Identifying the full landscape of small and medium-sized enterprises (SMEs) in specialized industry sectors is critical for supply-chain resilience,

arXiv:2604.28138v1 Announce Type: cross Abstract: Autonomous agents act through sandboxed containers and microVMs whose state spans filesystems, processes, and runtime artifacts. Checkpoint and restor

arXiv:2604.27137v1 Announce Type: new Abstract: This paper introduces a systematic evaluation framework grounded in the Interagency Language Roundtable (ILR) Skill Level Descriptions and applies it to

arXiv:2602.17469v2 Announce Type: replace Abstract: Recent advances in multilingual representation learning aim to bridge the performance gap between high- and low-resource languages, yet their abilit

arXiv:2603.09117v2 Announce Type: replace-cross Abstract: Reinforcement Learning from Verifiable Rewards (RLVR) significantly enhances large language models (LLMs) reasoning but severely suffers from

arXiv:2604.27929v1 Announce Type: new Abstract: With the widespread adoption of large language models (LLMs), understanding their personality representation mechanisms has become critical. As a novel

arXiv:2604.27453v1 Announce Type: new Abstract: Large language models have achieved remarkable progress in text generation but still struggle with generative writing tasks. In terms of evaluation, exi

arXiv:2604.28196v1 Announce Type: new Abstract: Driving world models serve as a pivotal technology for autonomous driving by simulating environmental dynamics. However, existing approaches predominant

arXiv:2604.16399v2 Announce Type: replace-cross Abstract: The widespread adoption of AI-assisted development tools in 2025 -- and the emergence of vibe coding, a practice of generating complete applic

arXiv:2601.00376v2 Announce Type: replace-cross Abstract: Repository-level code generation has attracted growing attention in recent years. Unlike function-level code generation, it requires the model

arXiv:2604.27724v1 Announce Type: new Abstract: Medical retrieval-augmented generation (RAG) systems typically operate on text chunks extracted from biomedical literature, discarding the rich visual c

arXiv:2604.27366v1 Announce Type: new Abstract: Recent advances in vision language action (VLA) models have shown remarkable potential for autonomous driving by directly mapping multimodal inputs to c

arXiv:2604.26963v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as the execution core of autonomous agents rather than as standalone text generators. Agentic w

arXiv:2604.28061v1 Announce Type: cross Abstract: Numerous metascience studies and other initiatives have begun to monitor the prevalence of open science practices when it is more important to underst

arXiv:2604.27733v1 Announce Type: new Abstract: Preference learning has become the foundation of aligning Large Language Models (LLMs) with human intent. Popular methods, such as Direct Preference Opt

arXiv:2604.26984v1 Announce Type: new Abstract: Representational collapse, where embeddings become anisotropic and lose multi-scale structure, can erode downstream performance long before performance

arXiv:2604.27846v1 Announce Type: new Abstract: How people narrate their experiences offers a window into how the mind organizes them. Computational approaches to therapeutic writing have evolved from

📢 Official Announcement: Qwen Partners with Fireworks AI to Accelerate Access to Qwen Family Models We are pleased to announce a strategic partnership between Qwen and Fireworks AI to deliver optimize

arXiv:2604.27723v1 Announce Type: new Abstract: Learning algorithms can be significantly improved by routing complex or uncertain inputs to specialized experts, balancing accuracy with computational c

arXiv:2604.27311v1 Announce Type: cross Abstract: The advent of Large Language Models (LLMs) has significantly transformed tasks across Software Engineering. In the context of Business Process Managem

arXiv:2604.27616v1 Announce Type: new Abstract: People commonly leverage structured content to accelerate knowledge acquisition and research problem solving. Among these, roadmaps guide researchers th

arXiv:2604.27780v1 Announce Type: cross Abstract: Large Language Models (LLMs) have rapidly improved in performance across code-related tasks, making their integration into Register Transfer Level (RT

arXiv:2604.27096v1 Announce Type: new Abstract: The purpose of our paper is to develop a unified multi-agent architecture that automates end-to-end machine learning (ML) pipeline generation from datas

arXiv:2604.27132v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) and Multi-Agent Systems (MAS) in high-stakes domains demand reliable verification, yet centralized approaches suffer four

arXiv:2604.27491v1 Announce Type: new Abstract: Modeling 4D human-object interaction (HOI) is a compelling challenge in computer vision and an essential technology powering virtual and mixed-reality a

arXiv:2510.08278v3 Announce Type: replace Abstract: Embodied Reference Understanding requires identifying a target object in a visual scene based on both language instructions and pointing cues. While

arXiv:2604.26703v1 Announce Type: cross Abstract: Standard density functional theory (DFT) routinely misclassifies the electronic ground state of correlated and structurally complex compounds, predict

arXiv:2509.11058v2 Announce Type: replace Abstract: Zero-Shot Video Anomaly Detection (ZS-VAD) requires temporally localizing anomalies without target domain training data, which is a crucial task due

arXiv:2601.11568v2 Announce Type: replace-cross Abstract: Training Large Language Models (LLMs) is highly memory-intensive due to optimizer state overhead. The FRUGAL framework mitigates this with gra

The search did not return specific details about release b8982. Based on the llama.cpp project context from the search results, b8982 is a build/release version from the llama.cpp repository that foll