8 papers
Sandwich Reasoning: An Answer-Reasoning-Answer Approach for Low-Latency Query Correction
Chen Zhang, Kepu Zhang, Jiatong Zhang +2
Query correction is a critical entry point in modern search pipelines, demanding high accuracy strictly within real-time latency constraints. Chain-of-Thought (CoT) reasoning impro…
PrLM: Learning Explicit Reasoning for Personalized RAG via Contrastive Reward Optimization
Kepu Zhang, Teng Shi, Weijie Yu +1
Personalized retrieval-augmented generation (RAG) aims to produce user-tailored responses by incorporating retrieved user profiles alongside the input query. Existing methods prima…
An Explicit Syllogistic Legal Reasoning Framework for Large Language Models
Kepu Zhang, Weijie Yu, Zhongxiang Sun +1
Syllogistic reasoning is crucial for sound legal decision-making, allowing legal professionals to draw logical conclusions by applying general principles to specific case facts. Wh…
QE-RAG: A Robust Retrieval-Augmented Generation Benchmark for Query Entry Errors
Kepu Zhang, Zhongxiang Sun, Weijie Yu +5
Retriever-augmented generation (RAG) has become a widely adopted approach for enhancing the factual accuracy of large language models (LLMs). While current benchmarks evaluate the…
Legal Mathematical Reasoning with LLMs: Procedural Alignment through Two-Stage Reinforcement Learning
Kepu Zhang, Guofu Xie, Weijie Yu +4
Legal mathematical reasoning is essential for applying large language models (LLMs) in high-stakes legal contexts, where outputs must be both mathematically accurate and procedural…
Trigger: Refining Query Correction via Adaptive Model Selector
Kepu Zhang, Zhongxiang Sun, Xiao Zhang +4
In search scenarios, user experience can be hindered by erroneous queries due to typos, voice errors, or knowledge gaps. Therefore, query correction is crucial for search engines.…