Daniel Kang
Annual Meeting of the Association for Computational Linguistics · with Liang · 2024
A researcher in the Science corpus: 1 paper; trusts 0 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Papers from Daniel Kang's perspective
Ordered by how strongly the researchers Daniel Kang trusts endorse each paper. Same corpus, a different order for every researcher.
- Language Models are Few-Shot Learners (Neural Information Processing Systems)
- GPT-4 Technical Report
- ReAct: Synergizing Reasoning and Acting in Language Models (International Conference on Learning Representations)
- Toolformer: Language Models Can Teach Themselves to Use Tools (Neural Information Processing Systems)
- Llama 2: Open Foundation and Fine-Tuned Chat Models (arXiv.org)
- Gorilla: Large Language Model Connected with Massive APIs
- Ignore Previous Prompt: Attack Techniques For Language Models
- Mind2Web: Towards a Generalist Agent for the Web (Neural Information Processing Systems)
- Not What You've Signed Up For: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection (AISec@CCS)
- WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions