Papers by Qingyao Yang

2 papers
LegalAgentBench: Evaluating LLM Agents in Legal Domain (2025.acl-long)

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Challenge: Existing general-domain benchmarks do not capture complexity of real-world judicial cognition and decision-making.
Approach: They propose a benchmark specifically designed to evaluate LLM Agents in the legal domain.
Outcome: The proposed benchmark includes 17 corpora from real-world legal scenarios and provides 37 tools for interacting with external knowledge.
Exploring Layer-wise Information Effectiveness for Post-Training Quantization in Small Language Models (2026.findings-acl)

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Challenge: Large language models with billions of parameters are often over-provisioned . smaller models exhibit lower robustness under extreme low-bit quantization .
Approach: They propose a hardware-native, metric-driven post-training quantization framework that keeps uniform bit-width within each layer while mixing precision across layers.
Outcome: LieQ reduces large accuracy gap observed for large language models with billions of parameters while preserving standard multiplication kernels.

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