arXiv (All)
open access
In-Place Instruction Following in Diffusion Language Models
Diffusion Large Language Models (dLLMs) generate text via bidirectional iterative denoising, naturally supporting user-specified constraints anchored at arbitrary output positions, a paradigm known as In-place Prompting (IPP). We formalize this as the In-place Instruction Following (IIF) task and co
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Lost with a Map: Conversational State and Behavioral Reliability in Language Models#1118956
- Speech Acts and Large Language Models#113584
- Enabling KV Caching of Shared Prefix for Diffusion Language Models#821900
- Trajectory-Level Speculative Decoding for Diffusion Language Models#780826
- Trajectory-Level Speculative Decoding for Diffusion Language Models#779451
Record · ID 975216
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive