Transcendence: Generative Models Can Outperform The Experts That Train Them

17 June 2024

Papers citing "Transcendence: Generative Models Can Outperform The Experts That Train Them"

8 / 8 papers shown

Title
Data-Efficient Multi-Agent Spatial Planning with LLMs Huangyuan Su Aaron Walsman Daniel Garces Sham Kakade Stephanie Gil LLMAG Presented at ResearchTrend Connect \| LLMAG on 28 Mar 2025 138 0 0 26 Feb 2025
Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges Nayoung Lee Ziyang Cai Avi Schwarzschild Kangwook Lee Dimitris Papailiopoulos ReLM VLM LRM AI4CE 80 4 0 03 Feb 2025
Provable Weak-to-Strong Generalization via Benign Overfitting David X. Wu A. Sahai 65 6 0 06 Oct 2024
EnsemW2S: Can an Ensemble of LLMs be Leveraged to Obtain a Stronger LLM? Aakriti Agrawal Mucong Ding Zora Che Chenghao Deng Anirudh Satheesh John Langford Furong Huang 45 4 0 06 Oct 2024
Human-aligned Chess with a Bit of Search Yiming Zhang Athul Paul Jacob Vivian Lai Daniel Fried Daphne Ippolito 26 1 0 04 Oct 2024
AI Safety in Generative AI Large Language Models: A Survey Jaymari Chua Yun Yvonna Li Shiyi Yang Chen Wang Lina Yao LM&MA 36 12 0 06 Jul 2024
Emergent World Models and Latent Variable Estimation in Chess-Playing Language Models Adam Karvonen 27 19 0 21 Mar 2024
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine Aviral Kumar George Tucker Justin Fu OffRL GP 337 1,955 0 04 May 2020