From Words to Numbers: Your Large Language Model Is Secretly A Capable
Regressor When Given In-Context Examples

From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples

11 April 2024

Robert Vacareanu

Vlad-Andrei Negru

Papers citing "From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples"

17 / 17 papers shown

Title
34 Examples of LLM Applications in Materials Science and Chemistry: Towards Automation, Assistants, Agents, and Accelerated Scientific Discovery Yoel Zimmermann Adib Bazgir Alexander H Al-Feghali Mehrad Ansari L. C. Brinson ... Shang Zhu Jan Janssen Calvin Li Ian Foster Ben Blaiszik 104 1 0 05 May 2025
Teaching Metric Distance to Autoregressive Multimodal Foundational Models Jiwan Chung Saejin Kim Yongrae Jo Jinho Park Dongjun Min Youngjae Yu 201 0 0 04 Mar 2025
Zero-shot Model-based Reinforcement Learning using Large Language Models Abdelhakim Benechehab Youssef Attia El Hili Ambroise Odonnat Oussama Zekri Albert Thomas Giuseppe Paolo Maurizio Filippone I. Redko Balázs Kégl OffRL 111 1 0 17 Feb 2025
Fourier Head: Helping Large Language Models Learn Complex Probability Distributions Nate Gillman Daksh Aggarwal Michael Freeman Saurabh Singh Chen Sun AI4TS 76 3 0 29 Oct 2024
ELICIT: LLM Augmentation via External In-Context Capability Futing Wang Jianhao Yan Yue Zhang Tao Lin 96 1 0 12 Oct 2024
InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation Gaurav Sahu Abhay Puri Juan A. Rodriguez Alexandre Drouin Perouz Taslakian ... Christopher Pal Nicolas Chapados I. Laradji Sai Rajeswar Mudumba Issam Hadj Laradji ELM 82 7 0 08 Jul 2024
Mixtral of Experts Albert Q. Jiang Alexandre Sablayrolles Antoine Roux A. Mensch Blanche Savary ... Théophile Gervet Thibaut Lavril Thomas Wang Timothée Lacroix William El Sayed MoE LLMAG 151 1,083 0 08 Jan 2024
In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering Sheng Liu Haotian Ye Lei Xing James Y. Zou 81 110 0 11 Nov 2023
Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions S. Bhattamishra Arkil Patel Phil Blunsom Varun Kanade 76 53 0 04 Oct 2023
Understanding In-Context Learning via Supportive Pretraining Data Xiaochuang Han Daniel Simig Todor Mihaylov Yulia Tsvetkov Asli Celikyilmaz Tianlu Wang AIMat 84 37 0 26 Jun 2023
Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection Yu Bai Fan Chen Haiquan Wang Caiming Xiong Song Mei 50 191 0 07 Jun 2023
Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer Yuandong Tian Yiping Wang Beidi Chen S. Du MLT 55 76 0 25 May 2023
RWKV: Reinventing RNNs for the Transformer Era Bo Peng Eric Alcaide Quentin G. Anthony Alon Albalak Samuel Arcadinho ... Qihang Zhao P. Zhou Qinghua Zhou Jian Zhu Rui-Jie Zhu 209 593 0 22 May 2023
Transformers learn in-context by gradient descent J. Oswald Eyvind Niklasson E. Randazzo João Sacramento A. Mordvintsev A. Zhmoginov Max Vladymyrov MLT 104 489 0 15 Dec 2022
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes Shivam Garg Dimitris Tsipras Percy Liang Gregory Valiant 131 505 0 01 Aug 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 874 12,916 0 04 Mar 2022
An Explanation of In-context Learning as Implicit Bayesian Inference Sang Michael Xie Aditi Raghunathan Percy Liang Tengyu Ma ReLM BDL VPVLM LRM 190 749 0 03 Nov 2021

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