Signals 4 · free daily AI digest

LLM2Jev: LLMs Are Already Jev-Style Decision Models -- When and How to Fine-Tune Them

Paper recorded by Signals 4 on 2026-10-01 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-01 on arXiv · recorded by Signals 4 on 2026-10-02

Category: cs.CL · 自然语言处理 · first seen 2026-10-02

Abstract

Jev-style decision models return categorical probability distributions over predefined options without generating free-form text, enabling software systems to act on their outputs directly. In this work, we investigate the extent to which general-purpose LLMs already possess this capability out of the box, and when fine-tuning is actually necessary. We present LLM2Jev, an architecture-preserving f

Read on arXiv →

#5 most recent of 311 cs.CL papers we have recorded · ↑ newer: Scalable, Transferable Meta-network for Data Selection Requires a Diff · ↓ older: Typological Alignment of Stack-Based Language Models on Mildly Context
Cite this page: LLM2Jev: LLMs Are Already Jev-Style Decision Models -- When and How to Fine-Tune Them: the #5 most recent of 311 cs.CL papers we have recorded (as of 2026-10-01). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/llm2jev-llms-are-already-jev-style-decision-models-when-and-how-to-fine-tune-the.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.CL papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions