5 citations · 17 across the 43 of their papers we have counts for
21 papers · 1 filter
Finding the Translation Switch: Discovering and Exploiting the Task-Initiation Features in LLMs
Xinwei Wu, Heng Liu, Xiaohu Zhao +6
Large Language Models (LLMs) frequently exhibit strong translation abilities, even without task-specific fine-tuning. However, the internal mechanisms governing this innate capabil…
Triplets Better Than Pairs: Towards Stable and Effective Self-Play Fine-Tuning for LLMs
Yibo Wang, Hai-Long Sun, Qing-Guo Chen +4
Recently, self-play fine-tuning (SPIN) has been proposed to adapt large language models to downstream applications with scarce expert-annotated data, by iteratively generating synt…
Challenging Multilingual LLMs: A New Taxonomy and Benchmark for Unraveling Hallucination in Translation
Xinwei Wu, Heng Liu, Jiang Zhou +5
Large Language Models (LLMs) have advanced machine translation but remain vulnerable to hallucinations. Unfortunately, existing MT benchmarks are not capable of exposing failures i…
DeepWideSearch: Benchmarking Depth and Width in Agentic Information Seeking
Tian Lan, Bin Zhu, Qianghuai Jia +6
Current search agents fundamentally lack the ability to simultaneously perform \textit{deep} reasoning over multi-hop retrieval and \textit{wide}-scale information collection-a cri…
Scaling Beyond Context: A Survey of Multimodal Retrieval-Augmented Generation for Document Understanding
Sensen Gao, Shanshan Zhao, Xu Jiang +7
Document understanding is critical for applications from financial analysis to scientific discovery. Current approaches, whether OCR-based pipelines feeding Large Language Models (…
Marco-Voice Technical Report
Fengping Tian, Chenyang Lyu, Xuanfan Ni +8
This paper presents a multifunctional speech synthesis system that integrates voice cloning and emotion control speech synthesis within a unified framework. The goal of this work i…
Marco-Bench-MIF: On Multilingual Instruction-Following Capability of Large Language Models
Bo Zeng, Chenyang Lyu, Sinuo Liu +14
Instruction-following capability has become a major ability to be evaluated for Large Language Models (LLMs). However, existing datasets, such as IFEval, are either predominantly m…
ComfyUI-R1: Exploring Reasoning Models for Workflow Generation
Zhenran Xu, Yiyu Wang, Xue Yang +5
AI-generated content has evolved from monolithic models to modular workflows, particularly on platforms like ComfyUI, enabling customization in creative pipelines. However, craftin…
ComfyUI-Copilot: An Intelligent Assistant for Automated Workflow Development
Zhenran Xu, Xue Yang, Yiyu Wang +7
We introduce ComfyUI-Copilot, a large language model-powered plugin designed to enhance the usability and efficiency of ComfyUI, an open-source platform for AI-driven art creation.…
TransBench: Benchmarking Machine Translation for Industrial-Scale Applications
Haijun Li, Tianqi Shi, Zifu Shang +13
Machine translation (MT) has become indispensable for cross-border communication in globalized industries like e-commerce, finance, and legal services, with recent advancements in…
The Bitter Lesson Learned from 2,000+ Multilingual Benchmarks
Minghao Wu, Weixuan Wang, Sinuo Liu +7
As large language models (LLMs) continue to advance in linguistic capabilities, robust multilingual evaluation has become essential for promoting equitable technological progress.…
New Trends for Modern Machine Translation with Large Reasoning Models
Sinuo Liu, Chenyang Lyu, Minghao Wu +4
Recent advances in Large Reasoning Models (LRMs), particularly those leveraging Chain-of-Thought reasoning (CoT), have opened brand new possibility for Machine Translation (MT). Th…
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.…
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…
Chinese SafetyQA: A Safety Short-form Factuality Benchmark for Large Language Models
Yingshui Tan, Boren Zheng, Baihui Zheng +9
With the rapid advancement of Large Language Models (LLMs), significant safety concerns have emerged. Fundamentally, the safety of large language models is closely linked to the ac…
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…
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…
PMMT: Preference Alignment in Multilingual Machine Translation via LLM Distillation
Shuqiao Sun, Yutong Yao, Peiwen Wu +2
Translation is important for cross-language communication, and many efforts have been made to improve its accuracy. However, less investment is conducted in aligning translations w…
Building Decision Making Models Through Language Model Regime
Yu Zhang, Haoxiang Liu, Feijun Jiang +2
We propose a novel approach for decision making problems leveraging the generalization capabilities of large language models (LLMs). Traditional methods such as expert systems, pla…
Wings: Learning Multimodal LLMs without Text-only Forgetting
Yi-Kai Zhang, Shiyin Lu, Yang Li +7
Multimodal large language models (MLLMs), initiated with a trained LLM, first align images with text and then fine-tune on multimodal mixed inputs. However, the MLLM catastrophical…
Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees
Sijia Chen, Yibo Wang, Yi-Feng Wu +5
Tool-augmented large language models (LLMs) leverage tools, often in the form of APIs, to improve their reasoning capabilities on complex tasks. This enables them to act as intelli…