SAILER: structure-aware pre-trained language model for legal case retrieval
Legal case retrieval, which aims to find relevant cases for a query case, plays a core role in
the intelligent legal system. Despite the success that pre-training has achieved in ad-hoc …
the intelligent legal system. Despite the success that pre-training has achieved in ad-hoc …
Constructing tree-based index for efficient and effective dense retrieval
Recent studies have shown that Dense Retrieval (DR) techniques can significantly improve
the performance of first-stage retrieval in IR systems. Despite its empirical effectiveness, the …
the performance of first-stage retrieval in IR systems. Despite its empirical effectiveness, the …
An intent taxonomy of legal case retrieval
Legal case retrieval is a special Information Retrieval (IR) task focusing on legal case
documents. Depending on the downstream tasks of the retrieved case documents, users' …
documents. Depending on the downstream tasks of the retrieved case documents, users' …
Thuir@ coliee 2023: Incorporating structural knowledge into pre-trained language models for legal case retrieval
Legal case retrieval techniques play an essential role in modern intelligent legal systems. As
an annually well-known international competition, COLIEE is aiming to achieve the state-of …
an annually well-known international competition, COLIEE is aiming to achieve the state-of …
Unsupervised real-time hallucination detection based on the internal states of large language models
Hallucinations in large language models (LLMs) refer to the phenomenon of LLMs
producing responses that are coherent yet factually inaccurate. This issue undermines the …
producing responses that are coherent yet factually inaccurate. This issue undermines the …
Dragin: Dynamic retrieval augmented generation based on the real-time information needs of large language models
Dynamic retrieval augmented generation (RAG) paradigm actively decides when and what
to retrieve during the text generation process of Large Language Models (LLMs). There are …
to retrieve during the text generation process of Large Language Models (LLMs). There are …
Unbiased Learning to Rank Meets Reality: Lessons from Baidu's Large-Scale Search Dataset
Unbiased learning-to-rank (ULTR) is a well-established framework for learning from user
clicks, which are often biased by the ranker collecting the data. While theoretically justified …
clicks, which are often biased by the ranker collecting the data. While theoretically justified …
When Search Engine Services meet Large Language Models: Visions and Challenges
Combining Large Language Models (LLMs) with search engine services marks a significant
shift in the field of services computing, opening up new possibilities to enhance how we …
shift in the field of services computing, opening up new possibilities to enhance how we …
THUIR@ COLIEE 2023: more parameters and legal knowledge for legal case entailment
This paper describes the approach of the THUIR team at the COLIEE 2023 Legal Case
Entailment task. This task requires the participant to identify a specific paragraph from a …
Entailment task. This task requires the participant to identify a specific paragraph from a …
Mitigating Entity-Level Hallucination in Large Language Models
The emergence of Large Language Models (LLMs) has revolutionized how users access
information, shifting from traditional search engines to direct question-and-answer …
information, shifting from traditional search engines to direct question-and-answer …