Added llm tool papers

autogpts/forge/tutorials/005_adding_abilities.md

@@ -31,8 +31,27 @@
 - Preparing Your Agent for Ability Integration and Enhancement
 
 ## Additional Resources
-- Links to Documentation and Ability Development Guides
-- Community Discussions on Ability Development
+
+From **The Rise and Potential of Large Language Model Based Agents: A Survey** *Zhiheng Xi (Fudan University) et al. arXiv.* [[paper](https://arxiv.org/abs/2305.14497)] [[code](https://github.com/woooodyy/llm-agent-paper-list)]
+### Research Papers
+- [2023/07] **ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs.** *Yujia Qin et al. arXiv.* [[paper](https://arxiv.org/abs/2307.16789)] [[code](https://github.com/openbmb/toolbench)] [[dataset](https://paperswithcode.com/dataset/toolbench)]
+- [2023/05] **Large Language Models as Tool Makers.** *Tianle Cai et al. arXiv.* [[paper](https://arxiv.org/abs/2305.17126)] [[code](https://github.com/ctlllll/llm-toolmaker)]
+- [2023/05] **CREATOR: Disentangling Abstract and Concrete Reasonings of Large Language Models through Tool Creation.** *Cheng Qian et al. arXiv.* [[paper](https://arxiv.org/abs/2305.14318)]
+- [2023/04] **Tool Learning with Foundation Models.** *Yujia Qin et al. arXiv.* [[paper](https://arxiv.org/abs/2304.08354)] [[code](https://github.com/openbmb/bmtools)]
+- [2023/04] **ChemCrow: Augmenting large-language models with chemistry tools.** *Andres M Bran (Laboratory of Artificial Chemical Intelligence, ISIC, EPFL) et al. arXiv.* [[paper](https://arxiv.org/abs/2304.05376)] [[code](https://github.com/ur-whitelab/chemcrow-public)]
+- [2023/04] **GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical Information.** *Qiao Jin, Yifan Yang, Qingyu Chen, Zhiyong Lu. arXiv.* [[paper](https://arxiv.org/abs/2304.09667)] [[code](https://github.com/ncbi/GeneGPT)]
+- [2023/04] **OpenAGI: When LLM Meets Domain Experts.** *Yingqiang Ge et al. arXiv.* [[paper](https://arxiv.org/abs/2304.04370)] [[code](https://github.com/agiresearch/openagi)]
+- [2023/03] **HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face.** *Yongliang Shen et al. arXiv.* [[paper](https://arxiv.org/abs/2303.17580)] [[code](https://github.com/microsoft/JARVIS)]
+- [2023/03] **Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models.** *Chenfei Wu et al. arXiv.* [[paper](https://arxiv.org/abs/2303.04671)] [[code](https://github.com/microsoft/visual-chatgpt)]
+- [2023/02] **Augmented Language Models: a Survey.** *Grégoire Mialon et al. arXiv.* [[paper](https://arxiv.org/abs/2302.07842)]
+- [2023/02] **Toolformer: Language Models Can Teach Themselves to Use Tools.** *Timo Schick et al. arXiv.* [[paper](https://arxiv.org/abs/2302.04761)]
+- [2022/05] **TALM: Tool Augmented Language Models.** *Aaron Parisi et al. arXiv.* [[paper](https://arxiv.org/abs/2205.12255)]
+- [2022/05] **MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning.** *Ehud Karpas et al. arXiv.* [[paper](https://arxiv.org/abs/2205.00445)]
+- [2022/04] **Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.** *Michael Ahn et al. arXiv.* [[paper](https://arxiv.org/abs/2204.01691)] 
+- [2021/12] **WebGPT: Browser-assisted question-answering with human feedback.** *Reiichiro Nakano et al. arXiv.* [[paper](https://arxiv.org/abs/2112.09332)]
+- [2021/07] **Evaluating Large Language Models Trained on Code.** *Mark Chen et al. arXiv.* [[paper](https://arxiv.org/abs/2107.03374)] [[code](https://github.com/openai/human-eval)]
+
+
 
 ## Appendix
 - Examples of Ability Implementations