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Tasks over Application Manuals: Revealing Gaps in Long-Horizon Procedural Reasoning for Language Models

Paper recorded by Signals 4 on 2026-09-11 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-11 on arXiv · recorded by Signals 4 on 2026-09-14

Category: cs.CL · 自然语言处理 · first seen 2026-09-14

Abstract

Large language models (LLMs) have achieved strong performance on a wide range of natural language tasks, and recent benchmarks suggest that they are increasingly adept at multi-hop reasoning. However, these benchmarks are typically short-horizon, requiring only a small number of retrieval or inference steps, and provide limited evidence of reliability on real-world tasks that involve following man

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#55 most recent of 186 cs.CL papers we have recorded · ↑ newer: Kraken: LLM-based Speech-to-Speech Translation via Low-bitrate VQ and · ↓ older: Judging by the Cover: Cleaning LLM Truthfulness Benchmarks to Avoid Su
Cite this page: Tasks over Application Manuals: Revealing Gaps in Long-Horizon Procedural Reasoning for Language Models: the #55 most recent of 186 cs.CL papers we have recorded (as of 2026-09-11). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/tasks-over-application-manuals-revealing-gaps-in-long-horizon-procedural-reasoni.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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