Update README.md

Added first version of readme

README.md

@@ -1,3 +1,51 @@
----
-license: mit
----
+---
+license: mit
+task_categories:
+- question-answering
+language:
+- en
+tags:
+- finance
+- table-text
+- numerical_reasoning
+size_categories:
+- < 1K
+---
+
+
+# SECQUE
+
+- [**Paper**](https://arxiv.org/abs/2504.04596)
+
+SECQUE is a comprehensive benchmark for evaluating large language models (LLMs) in financial analysis tasks.
+
+SECQUE comprises 565 expert-written questions covering SEC filings analysis across four key categories: 
+- comparison analysis
+- ratio calculation
+- risk assessment
+- financial insight generation.
+
+To assess model performance, we develop SECQUE-Judge, an evaluation mechanism leveraging multiple LLM-based judges, which demonstrates strong alignment with human evaluations. 
+Additionally, we provide an extensive analysis of various models’ performance on our benchmark. 
+
+## Citation
+
+```bash
+@inproceedings{zhu2021tat,
+    title = "SECQUE: A Benchmark for Evaluating Real-World Financial Analysis Capabilitiese",
+    author = "Ben Yoash, Noga  and
+      Brief, Meni and
+      Ovadia, Oded  and
+      Shenderovitz, Gil  and
+      Mishaeli, Moshik  and
+      Lemberg, Rachel  and
+      Sheetrit, Eitam",
+    month = apr,
+    year = "2025",
+    url = "https://arxiv.org/pdf/2504.04596",
+}
+```
+
+## Evaluation Benchmark notice
+
+This benchmark is indented solely for evaluation, and must not be used for training in any way.