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BackTrend: Evaluating Scientific Weak-Signal Prediction via Backward Reconstruction

Paper recorded by Signals 4 on 2026-09-21 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-21 on arXiv · recorded by Signals 4 on 2026-09-22

Category: cs.AI · 人工智能 · first seen 2026-09-22

Abstract

Scientific weak signals are early, low-visibility research directions that later become central to mature scientific topics, yet existing resources such as trend tracking, citation forecasting, and foresight reports rarely provide validated reference sets that link concrete early precursors to later paradigms. We introduce BackTrend, a retrospective benchmark in which, given a mature target topic

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#13 most recent of 340 cs.AI papers we have recorded · ↑ newer: Et Tu, Brute? Economic Misalignment in Personal AI Agents · ↓ older: Visuomotor Robotic Pruning in Planar Orchards Using Hybrid Reinforceme
Cite this page: BackTrend: Evaluating Scientific Weak-Signal Prediction via Backward Reconstruction: the #13 most recent of 340 cs.AI papers we have recorded (as of 2026-09-21). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/backtrend-evaluating-scientific-weak-signal-prediction-via-backward-reconstructi.html
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