← Search

Liangying Shao

4 accepted papers

2025

Marco-o1 v2: Towards Widening The Distillation Bottleneck for Reasoning Models

ACL 2025long

Large Reasoning Models (LRMs) such as OpenAI o1 and DeepSeek-R1 have shown remarkable reasoning capabilities by scaling test-time compute and generating long Chain-of-Thought (CoT). Distillation post-training on LRMs-generated data is a straightforward yet effective method to enhance the reasoning a…

Cited by 0SourcePDFScholar
2024

Multi-Level Cross-Modal Alignment for Speech Relation Extraction

EMNLP 2024main

Speech Relation Extraction (SpeechRE) aims to extract relation triplets from speech data. However, existing studies usually use synthetic speech to train and evaluate SpeechRE models, hindering the further development of SpeechRE due to the disparity between synthetic and real speech. Meanwhile, the…

Cited by 0SourcePDFScholar
2024

One2Set + Large Language Model: Best Partners for Keyphrase Generation

EMNLP 2024main

Keyphrase generation (KPG) aims to automatically generate a collection of phrases representing the core concepts of a given document. The dominant paradigms in KPG include one2seq and one2set. Recently, there has been increasing interest in applying large language models (LLMs) to KPG. Our prelimina…

2023

A Sequence-to-Sequence&Set Model for Text-to-Table Generation

ACL 2023findings

Recently, the text-to-table generation task has attracted increasing attention due to its wide applications. In this aspect, the dominant model formalizes this task as a sequence-to-sequence generation task and serializes each table into a token sequence during training by concatenating all rows in…