「RAG」の検索結果
53 件このリポジトリでは、AIアプリケーションをローカルに実行できるツールキットであるRunAnywhere-sdksを提供しています。
BERTopicでは、BERTとc-TF-IDFを用いて、トピックを簡単に分析して解釈できるようにしたモデルを紹介しています。
Reliable video generation requires more than high-quality frames to form a coherent story: a model must mainta
Agent memory systems have demonstrated significant potential in long-term dialogue, personalized assistants, a
We study scheming in LLM agents, in which agents covertly pursue misaligned goals. Our focus is to understand
Remote sensing multimodal large language models (RS-MLLMs) have advanced scene understanding and visual questi
Vision transformers (ViTs) have achieved remarkable generalization across visual domains, yet little is known
Multiple Instance Learning (MIL) is widely used for weakly supervised learning, particularly in digital pathol
The software supply chain has become an increasingly exposed attack surface because of its reliance on intrica
Key--value (KV) cache compression is an effective way to reduce the memory overhead of large language model (L
Chain-of-thought (CoT) reasoning improves the reasoning ability of large language models by introducing interm
Financial scenarios are diverse and complex, spanning varying data conditions, tool configurations, and workfl
Taxonomy induction aims to organize concept sets into coherent hierarchical structures. Recent LLM-based metho
Ethical evaluation of Large Language Models (LLMs) often characterizes model values as static and monolithic.
Retrieval-augmented generation (RAG) enables large language models (LLMs) to answer questions by accessing ext
Out-of-distribution (OOD) detection is critical for safe deployment of medical AI systems. Recently, test-time
Large Vision-Language Models (LVLMs) have achieved strong performance on diverse visual tasks, yet their abili
Target-based LiDAR-camera extrinsic calibration is a prerequisite for multi-sensor fusion in robotics. However
Robotic manipulation often requires acting on information that is no longer visible, yet Vision-Language-Actio
Authorship signals matter in settings where writing style carries identity: digital forensics, plagiarism anal
Video foundation models increasingly rely on large-scale pretraining data, yet the end-to-end data pipelines b
Most end-to-end autonomous-driving systems learn by imitating human driving logs, leaving their learned behavi
Agents can turn shared infrastructure into a channel for coordinated intrusion. The Hugging Face incident and
World-action models guide action generation with predicted future observations, but vision-centric predictions
We present a continuous, population-scale measurement record of autonomous language-model trading agents opera
医学画像に対する疾患検出モデルを開発し、臨床現場で早期検出と迅速な介入を容易にすることを目的としたフレームワークを提案します。
A reasoning model can improve from its own on-policy experience, but this inner loop is fragile: terminal veri
We present ENEAS, a unified, text-promptable method for instance tracking and semantic discovery. Text-prompta
Safety alignment is usually posed as a topic-level question: is this subject harmful? Deployments ask a narrow
Audio-video diffusion models rely on cross-modal attention to coordinate text, sound, and visual content, yet
Designing and authoring high-performance custom kernels for accelerators is a complex task that requires deep
Large language models (LLMs) are increasingly used to edit existing code, but correctness alone is not enough:
Quantization is widely used to reduce the computational and memory demands of neural-network inference. In rec
Large language models achieve superior performance on tasks that require extended reasoning, but long chains o
On-policy distillation (OPD) combines student-generated rollouts with dense token-level supervision from a tea
Hybrid LLMs pair softmax attention with linear-attention layers such as Gated DeltaNet (GDN), whose recurrent
Online 3D reconstruction models perform poorly on long videos. This happens because regressing poses relative
Streaming video understanding requires multimodal large language models (MLLMs) to process continuous visual i
MLLM-based embedding models remain limited in compositional retrieval, often failing to distinguish scenes con
On-policy distillation (OPD) accelerates post-training by providing dense token-level supervision from a froze
Streaming video understanding is a critical capability for real-world applications, including embodied intelli
Reconstructing a damaged musical fragment is an inverse problem: the observed sequence contains partial inform
Vision-language-action (VLA) models map visual observations and language instructions directly to robot action
Command-line coding agents (e.g., Claude Code, Gemini CLI) can already read and write files and sustain long s
Coding agents are now commonly evaluated on the SWE-bench family of benchmarks, whose tasks are built from cur
Text-driven 3D generation has advanced rapidly in creating large-scale outdoor environments and detailed indoo
Reinforcement learning with verifiable rewards (RLVR) substantially improves single-sample accuracy (pass@1) b
In this paper, we introduce ES-AHD, a novel framework that fundamentally integrates Evolution Strategy (ES) in
このリポジトリには、LLM、RAG、およびオーソリティの認識を含む、AIエンジニアリングのための深いドキュメントがあります。
Change data synthesis provides a cost-effective solution for expanding training data and improving the perform
GUI操作自動化に伴う停止判定、復讐、再検索に関する問題を解決し、 GUI操作自動化を実現するためのフレームワークを開発します。
Audio-visual understanding remains challenging because models must jointly interpret spoken content, visual ev
Particle swarm optimization (PSO) is a widely used metaheuristic, prized for its simplicity and small paramete