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Jul 9, 2023
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6 changes: 4 additions & 2 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -86,7 +86,7 @@ For the **latest version** of the paper, keep an eye on the [releases](https://g

#### Natural language understanding

##### Setiment analysis
##### Sentiment analysis
1. Holistic evaluation of language models. _Percy Liang et al._ arXiv 2022. [[paper](https://arxiv.org/abs/2211.09110)]
2. Can chatgpt forecast stock price movements? return predictability and large language models. _Alejandro Lopez-Lira et al._ SSRN 2023. [[paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4412788)]
3. Is chatgpt a general-purpose natural language processing task solver? _Chengwei Qin et al._ arXiv 2023. [[paper](https://arxiv.org/abs/2302.06476)]
Expand Down Expand Up @@ -120,6 +120,8 @@ For the **latest version** of the paper, keep an eye on the [releases](https://g
8. Are large language models really good logical reasoners? a comprehensive evaluation from deductive, inductive and abductive views. _Fangzhi Xu et al._ arXiv 2023. [[paper](https://arxiv.org/abs/2306.09841)]
9. Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4. _Hanmeng Liu et al._ arXiv 2023. [[paper](https://arxiv.org/abs/2304.03439)]
10. A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets, _Laskar et al._ ACL 2023 (Findings). [[paper](https://arxiv.org/abs/2305.18486)]
11. MindGames: Targeting Theory of Mind in Large Language Models with Dynamic Epistemic Modal Logic _Sileo et Lernould_ arXiv 2023. [[paper](https://arxiv.org/abs/2305.03353)]


#### Natural language generation

Expand Down Expand Up @@ -359,4 +361,4 @@ If you find this project useful in your research or work, please consider citing

1. Tahmid Rahman ([@tahmedge](https://github.com/tahmedge)) for [PR#1](https://github.com/MLGroupJLU/LLM-eval-survey/pull/1).
2. Hao Zhao for suggestions on new benchmarks.
3. Chenhui Zhang for suggestions on robustness, ethics, and trustworthiness.
3. Chenhui Zhang for suggestions on robustness, ethics, and trustworthiness.