2305.18654

N/A

Faith and Fate: Limits of Transformers on Compositionality Nouha Dziri1∗ , Ximing Lu1,2∗ , Melanie Sclar2∗ , Xiang Lorraine Li1† , Liwei Jiang1,2† , Bill Yuchen Lin1† , Peter West1,2 , Chandra Bhagavatula1 , Ronan Le Bras1 , Jena D. Hwang1 , Soumya Sanyal3 , arXiv:2305.18654v3 [cs.CL] 31 Oct 2023 Sean Welleck1,2…

saved by

• elwkmg mewpog3m

related reading

• 2305.18654.pdfarxiv.org
• [2305.18654] Faith and Fate: Limits of Transformers on Compositionalityarxiv.org
• A Mathematical Framework for Transformer Circuitstransformer-circuits.pub
• 2402.12875arxiv.org
• [2510.13786] The Art of Scaling Reinforcement Learning Compute for LLMsarxiv.org
• [2201.11903] Chain of Thought Prompting Elicits Reasoning in Large Language Modelsarxiv.org
• [2404.15758] Let's Think Dot by Dot: Hidden Computation in Transformer Language Modelsarxiv.org
• [2005.14165] Language Models are Few-Shot Learnersarxiv.org
• Reasoning Models Reason Well, Until They Don'tarxiv.org
• 2306.17806arxiv.org
• [2310.16028] What Algorithms can Transformers Learn? A Study in Length Generalizationarxiv.org
• [2210.13382] Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Taskarxiv.org