8 citations · 20 across the 29 of their papers we have counts for
20 papers · 1 filter
WnW: Waxing-and-Waning KV Cache for Long-Form Speech LLMs
Yiming Yao, Chenyang Lyu, Xuanfan Ni +4
Long-form audio inputs make the KV cache the dominant memory cost of speech LLMs. Prefill-only KV compression methods permanently discard audio KV positions once evicted, with no p…
SemEval-2026 Task 7: Everyday Knowledge Across Diverse Languages and Cultures
Nedjma Ousidhoum, Junho Myung, Carla Perez-Almendros +27
We present our shared task on evaluating the adaptability of LLMs and NLP systems across multiple languages and cultures. The task data consist of an extended version of our manual…
Marco-MoE: Open Multilingual Mixture-of-Expert Language Models with Efficient Upcycling
Fan Jiang, Yu Zhao, Chenyang Lyu +5
We present Marco-MoE, a suite of fully open multilingual sparse Mixture-of-Experts (MoE) models. Marco-MoE features a highly sparse design in which only around 5\% of the total par…
CulturALL: Benchmarking Multilingual and Multicultural Competence of LLMs on Grounded Tasks
Peiqin Lin, Chenyang Lyu, Wenjiang Luo +22
Large language models (LLMs) are now deployed worldwide, inspiring a surge of benchmarks that measure their multilingual and multicultural abilities. However, these benchmarks prio…
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…
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.…
ReFreeKV: Towards Threshold-Free KV Cache Compression
Xuanfan Ni, Liyan Xu, Chenyang Lyu +6
To reduce memory consumption during LLM inference, a handful of methods have been proposed for KV cache pruning. While these techniques can accomplish lossless memory reduction on…
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…
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…
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…
Reference-free Hallucination Detection for Large Vision-Language Models
Qing Li, Jiahui Geng, Chenyang Lyu +3
Large vision-language models (LVLMs) have made significant progress in recent years. While LVLMs exhibit excellent ability in language understanding, question answering, and conver…
From Multiple-Choice to Extractive QA: A Case Study for English and Arabic
Teresa Lynn, Malik H. Altakrori, Samar Mohamed Magdy +11
The rapid evolution of Natural Language Processing (NLP) has favoured major languages such as English, leaving a significant gap for many others due to limited resources. This is e…
Beyond Probabilities: Unveiling the Misalignment in Evaluating Large Language Models
Chenyang Lyu, Minghao Wu, Alham Fikri Aji
Large Language Models (LLMs) have demonstrated remarkable capabilities across various applications, fundamentally reshaping the landscape of natural language processing (NLP) resea…
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…
A Comprehensive Evaluation of GPT-4V on Knowledge-Intensive Visual Question Answering
Yunxin Li, Longyue Wang, Baotian Hu +5
The emergence of multimodal large models (MLMs) has significantly advanced the field of visual understanding, offering remarkable capabilities in the realm of visual question answe…