activity
20232025
most citedMarco-o1: Towards Open Reasoning Models for Open-Ended Solutions

5 citations · 15 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CL2025

Towards Lightweight, Adaptive and Attribute-Aware Multi-Aspect Controllable Text Generation with Large Language Models

Chenyu Zhu, Yefeng Liu, Chenyang Lyu +5

Multi-aspect controllable text generation aims to control text generation in attributes from multiple aspects, making it a complex but powerful task in natural language processing.…

cs.CL2025

LayAlign: Enhancing Multilingual Reasoning in Large Language Models via Layer-Wise Adaptive Fusion and Alignment Strategy

Zhiwen Ruan, Yixia Li, He Zhu +5

Despite being pretrained on multilingual corpora, large language models (LLMs) exhibit suboptimal performance on low-resource languages. Recent approaches have leveraged multilingu…

cs.CL2024

Findings of the WMT 2024 Shared Task on Discourse-Level Literary Translation

Longyue Wang, Siyou Liu, Chenyang Lyu +11

Following last year, we have continued to host the WMT translation shared task this year, the second edition of the Discourse-Level Literary Translation. We focus on three language…

cs.CL2024

Marco-LLM: Bridging Languages via Massive Multilingual Training for Cross-Lingual Enhancement

Lingfeng Ming, Bo Zeng, Chenyang Lyu +17

Large Language Models (LLMs) have achieved remarkable progress in recent years; however, their excellent performance is still largely limited to major world languages, primarily En…

cs.CL2024★ 5 cited

Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions

Yu Zhao, Huifeng Yin, Bo Zeng +6

Currently OpenAI o1 sparks a surge of interest in the study of large reasoning models (LRM). Building on this momentum, Marco-o1 not only focuses on disciplines with standard answe…

cs.CL2024★ 2 cited

Large Language Models as Code Executors: An Exploratory Study

Chenyang Lyu, Lecheng Yan, Rui Xing +4

The capabilities of Large Language Models (LLMs) have significantly evolved, extending from natural language processing to complex tasks like code understanding and generation. We…

cs.CL2024★ 1 cited

On the Information Redundancy in Non-Autoregressive Translation

Zhihao Wang, Longyue Wang, Jinsong Su +2

Token repetition is a typical form of multi-modal problem in fully non-autoregressive translation (NAT). In this work, we revisit the multi-modal problem in recently proposed NAT m…

cs.CL2023★ 1 cited

Retrieval-augmented Multi-modal Chain-of-Thoughts Reasoning for Large Language Models

Bingshuai Liu, Chenyang Lyu, Zijun Min +3

The advancement of Large Language Models (LLMs) has brought substantial attention to the Chain of Thought (CoT) approach, primarily due to its ability to enhance the capability of…

cs.CV2023★ 2 cited

Alternate Diverse Teaching for Semi-supervised Medical Image Segmentation

Zhen Zhao, Zicheng Wang, Longyue Wang +3

Semi-supervised medical image segmentation studies have shown promise in training models with limited labeled data. However, current dominant teacher-student based approaches can s…

cs.CV2023★ 4 cited

A Systematic Evaluation of GPT-4V's Multimodal Capability for Medical Image Analysis

Yingshu Li, Yunyi Liu, Zhanyu Wang +7

This work conducts an evaluation of GPT-4V's multimodal capability for medical image analysis, with a focus on three representative tasks of radiology report generation, medical vi…