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Flide: Accelerating Decision Inference with Exact State Forking

Paper recorded by Signals 4 on 2026-10-30 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-30 on arXiv · recorded by Signals 4 on 2026-11-02

Category: cs.CL · 自然语言处理 · first seen 2026-11-02

Abstract

Decision models such as Jev have emerged as a highly promising paradigm for LLM agent systems, providing lightweight and reliable categorical reasoning for rapid System One execution. However, existing generation-oriented inference engines fail to support these workloads effectively, suffering from severe prefix recomputation overheads or distorted output probabilities. To address this challenge,

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#43 most recent of 628 cs.CL papers we have recorded · ↑ newer: Which Words a Model Fears: From a Refusal Direction to a Vocabulary-Wi · ↓ older: DecisionRank: On-Policy Distillation for Decision-Model Rerankers
Cite this page: Flide: Accelerating Decision Inference with Exact State Forking: the #43 most recent of 628 cs.CL papers we have recorded (as of 2026-10-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/flide-accelerating-decision-inference-with-exact-state-forking.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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