AINewsnow

AgentSpec: Speculative Decoding for Batch Inference of LLM Agents

This story is from 2026-08-26. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2608.24004v1 Announce Type: new Abstract: Large language model (LLM)-based agent applications often incur high response time. Speculative decoding is a promising solution to improve the inference efficiency of LLM agents without impacting generation quality. However, state-of-the-art speculat…

Read the full story at arXiv cs.CL ↗

Timeline · 1 report

  1. 2026-08-26 04:00 · arXiv cs.CL
    AgentSpec: Speculative Decoding for Batch Inference of LLM Agents

More stories

  1. Introducing Kimi K3 on Amazon Bedrock — AWS Machine Learning Blog
  2. Introducing Amazon SageMaker HyperPod Inference Gateway — AWS Machine Learning Blog
  3. Anthropic, OpenAI, SpaceXAI, Google sued over call to ‘pace’ AI development — Politico Technology
  4. Gemini Hacked Three Companies in First Known Breakout by Google’s AI — Wall Street Journal Technology
  5. Alibaba ships Qwen3.8-Omni-Flash to watch, listen and call tools — r/LocalLLM
  6. NVIDIA CEO Jensen Huang rejects ‘AI will end the world’ claim, yet cautions ‘we should go as fast as we can but...’ — Mint AI
  7. Meet the Data Agent in ChatGPT Work — OpenAI YouTube
  8. Qwen Image 2.1 PR to ComfyUI — r/StableDiffusion

Get the daily brief of stories like this at 6:30 every morning →