Pre-trained Large Language Models Use Fourier Features to Compute Addition

5 June 2024

Papers citing "Pre-trained Large Language Models Use Fourier Features to Compute Addition"

9 / 9 papers shown

Title
Understanding In-context Learning of Addition via Activation Subspaces Xinyan Hu Kayo Yin Michael I. Jordan Jacob Steinhardt Lijie Chen 39 0 0 08 May 2025
Block Circulant Adapter for Large Language Models Xinyu Ding Meiqi Wang Siyu Liao Zhongfeng Wang 29 0 0 01 May 2025
Implicit Reasoning in Transformers is Reasoning through Shortcuts Tianhe Lin Jian Xie Siyu Yuan Deqing Yang ReLM LRM 64 2 0 10 Mar 2025
Investigating Compositional Reasoning in Time Series Foundation Models Willa Potosnak Cristian Challu Mononito Goswami Kin G. Olivares Michał Wiliński Nina Żukowska Artur Dubrawski ReLM AI4TS LRM 46 0 0 09 Feb 2025
Arithmetic Without Algorithms: Language Models Solve Math With a Bag of Heuristics Yaniv Nikankin Anja Reusch Aaron Mueller Yonatan Belinkov AIFin LRM 33 21 0 28 Oct 2024
Language Models Encode Numbers Using Digit Representations in Base 10 Amit Arnold Levy Mor Geva 19 4 0 15 Oct 2024
Composing Global Optimizers to Reasoning Tasks via Algebraic Objects in Neural Nets Yuandong Tian 44 0 0 02 Oct 2024
IsoBench: Benchmarking Multimodal Foundation Models on Isomorphic Representations Deqing Fu Ghazal Khalighinejad Ollie Liu Bhuwan Dhingra Dani Yogatama Robin Jia W. Neiswanger 25 14 0 01 Apr 2024
How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model Michael Hanna Ollie Liu Alexandre Variengien LRM 184 116 0 30 Apr 2023