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References (35)

[1]
CryptoBench: A Dynamic Benchmark for Expert-Level Evaluation of LLM Agents in Cryptocurrency
2025Jiacheng Guo, Suozhi Huang et al.
[2]
When Hallucination Costs Millions: Benchmarking AI Agents in High-Stakes Adversarial Financial Markets
2025Zeshi Dai, Zimo Peng et al.
[3]
Evaluation and Benchmarking of LLM Agents: A Survey
2025Mahmoud Mohammadi, Yipeng Li et al.
[4]
Evaluating Scoring Bias in LLM-as-a-Judge
2025Qingquan Li, Shaoyu Dou et al.
[5]
DRAGged into Conflicts: Detecting and Addressing Conflicting Sources in Search-Augmented LLMs
2025Arie Cattan, Alon Jacovi et al.
[6]
CiteEval: Principle-Driven Citation Evaluation for Source Attribution
2025Yumo Xu, Peng Qi et al.
[7]
Finance Agent Benchmark: Benchmarking LLMs on Real-world Financial Research Tasks
2025Antoine Bigeard, Langston Nashold et al.
[8]
DMind Benchmark: Toward a Holistic Assessment of LLM Capabilities across the Web3 Domain
2025Enhao Huang, Pengyu Sun et al.
[9]
BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents
2025Jason Wei, Zhiqing Sun et al.
[10]
INVESTORBENCH: A Benchmark for Financial Decision-Making Tasks with LLM-based Agent
2025Haohang Li, Yupeng Cao et al.
[11]
LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods
2024Haitao Li, Qian Dong et al.
[12]
Self-Preference Bias in LLM-as-a-Judge
2024Koki Wataoka, Tsubasa Takahashi et al.
[13]
Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge
2024Jiayi Ye, Yanbo Wang et al.
[14]
WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia
2024Yufang Hou, Alessandra Pascale et al.
[15]
From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline
2024Tianle Li, Wei-Lin Chiang et al.
[16]
Judging the Judges: A Systematic Study of Position Bias in LLM-as-a-Judge
2024Lin Shi, Chiyu Ma et al.
[17]
Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators
2024Yann Dubois, Bal'azs Galambosi et al.
[18]
How well do LLMs cite relevant medical references? An evaluation framework and analyses
2024Kevin Wu, Eric Wu et al.
[19]
What Do the Regulators Mean? A Taxonomy of Regulatory Principles for the Use of AI in Financial Services
2024Mustafa Pamuk, Matthias Schumann et al.
[20]
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2024Yuan Li, B. Luo et al.

Showing 20 of 35 references

Founder's Pitch

"Develop a robust benchmark and evaluation tool for LLMs in the crypto analysis domain to improve accuracy in high-stakes decision making."

LLM EvaluationScore: 7View PDF ↗

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0-10 scale

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2.5

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7.5

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3/4 signals

7.5

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