3k citations · 9.5k across the 23 of their papers we have counts for
4 papers · 2 filters
RTTC: Reward-Guided Collaborative Test-Time Compute
J. Pablo Muñoz, Jinjie Yuan
Test-Time Compute (TTC) has emerged as a powerful paradigm for enhancing the performance of Large Language Models (LLMs) at inference, leveraging strategies such as Test-Time Train…
Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning
Erxin Yu, Jing Li, Ming Liao +7
Although large language models demonstrate strong performance across various domains, they still struggle with numerous bad cases in mathematical reasoning. Previous approaches to…
SEA-LION: Southeast Asian Languages in One Network
Raymond Ng, Thanh Ngan Nguyen, Yuli Huang +28
Recently, Large Language Models (LLMs) have dominated much of the artificial intelligence scene with their ability to process and generate natural languages. However, the majority…
ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification
Yashwanth M., Vaibhav Singh, Ayush Maheshwari +2
We propose ARISE, a framework that iteratively induces rules and generates synthetic data for text classification. We combine synthetic data generation and automatic rule induction…