「RAG」の検索結果
19 件A reasoning model can improve from its own on-policy experience, but this inner loop is fragile: terminal veri
Audio-video diffusion models rely on cross-modal attention to coordinate text, sound, and visual content, yet
Hybrid LLMs pair softmax attention with linear-attention layers such as Gated DeltaNet (GDN), whose recurrent
Traditional speaker-attributed ASR systems treated ASR and speaker diarization as two separate tasks. Recently
Retrieval is the first stage of modern search and advertising systems, selecting a candidate set from a large
The attention prefilling phase of long-context LLM inference scales quadratically, making self-attention a sev
Embedding-based code retrieval is a core component of coding agents and retrieval-augmented code generation, w
Understanding animal motion is fundamental to modeling animal behavior and biomechanics, yet progress in this
Modern Text-to-SQL systems often follow generate-execute-select pipelines, generating multiple candidate queri
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
Information retrieval (IR) increasingly targets open-ended queries that admit diverse perspectives. Existing I
We present FoldingAgent, an agentic framework for inferring explicit parametric folding programs directly from
Mobile AI acts as a visual oracle, empowering users to snap a picture of something and ask for information. Sn
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
Change data synthesis provides a cost-effective solution for expanding training data and improving the perform
Knowledge-Based Visual Question Answering (KB-VQA) relies on retrieving external information to answer queries
Audio-visual understanding remains challenging because models must jointly interpret spoken content, visual ev