Files
agent/papers/items/2026-2605-20315-mix-quant-quantized-prefilling-precise-decoding-for-agentic-llms.md
2026-07-08 12:25:30 +08:00

65 lines
1.4 KiB
Markdown

# Paper: Mix-Quant: Quantized Prefilling, Precise Decoding for Agentic LLMs
---
type: paper
title: "Mix-Quant: Quantized Prefilling, Precise Decoding for Agentic LLMs"
authors: Haiquan Lu, Zigeng Chen, Gongfan Fang, Xinyin Ma, Xinchao Wang
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2605.20315
code_url:
source: arxiv
collected_at: 2026-07-08
published_at: 2026-05-19
updated_at: 2026-05-19
status: queued
relevance: high
topics:
- agent-evaluation
- coding-agent
- memory
- planning
- rag
- tool-use
- workflow-agent
methods:
-
benchmarks:
-
models:
-
datasets:
- cs.CL
related_concepts:
-
related_jobs:
-
related_experiments:
-
related_projects:
-
collection_score: 21
collection_queries: planning-agent
---
## One-line Takeaway
Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
## Why Collected
- matched queries: planning-agent
- inferred topics: agent-evaluation, coding-agent, memory, planning, rag, tool-use, workflow-agent
- arXiv categories: cs.CL
- collection score: 21
## Review Checklist
- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
- Does it include a benchmark, dataset, code, or reproducible experimental setup?
- Should it be promoted from `queued` to `skimmed` or `summarized`?
## Links
- arXiv: https://arxiv.org/abs/2605.20315