From the 1 of 22 linked papers with an AI index.
11 papers · 1 filter
PI-Mem: Pushing Long-Context Reasoning to 3.6M Tokens with Parallel-Iterative Memory
Dawei Liu, Haixu Song, Shuang Cheng +9
Long-context reasoning remains a critical bottleneck for large language models, as recent recurrent-memory approaches face two inherent challenges: sequential chunk-wise updates ca…
Frontis-MA1: Training an AI4AI Model towards Recursive Self-Improvement in Machine Learning Engineering
Junlin Yang, Che Jiang, Yu Fu +21
The paper presents Frontis-MA1, a 35‑billion‑parameter model trained as a meta‑evolution agent for machine learning engineering, using a new OpenMLE stack that combines operator le…
LFQA-E: Carefully Benchmarking Long-form QA Evaluation
Yuchen Fan, Chen Lin, Xin Zhong +11
Long-Form Question Answering (LFQA) involves generating comprehensive, paragraph-level responses to open-ended questions, which poses a significant challenge for evaluation due to…
A Survey of Reinforcement Learning for Large Reasoning Models
Kaiyan Zhang, Yuxin Zuo, Bingxiang He +36
In this paper, we survey recent advances in Reinforcement Learning (RL) for reasoning with Large Language Models (LLMs). RL has achieved remarkable success in advancing the frontie…
Intuitive Fine-Tuning: Towards Simplifying Alignment into a Single Process
Ermo Hua, Biqing Qi, Kaiyan Zhang +4
Supervised Fine-Tuning (SFT) and Preference Optimization (PO) are key processes for aligning Language Models (LMs) with human preferences post pre-training. While SFT excels in eff…
How to Synthesize Text Data without Model Collapse?
Xuekai Zhu, Daixuan Cheng, Hengli Li +7
Model collapse in synthetic data indicates that iterative training on self-generated data leads to a gradual decline in performance. With the proliferation of AI models, synthetic…