5 papers
: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation
Hao Wang, Linlong Xu, Heng Liu +12
Aligning Large Language Models (LLMs) with human preferences is pivotal for Machine Translation (MT), yet current approaches are often hindered by misleading reward signals. Our an…
Marco-o1 v2: Towards Widening The Distillation Bottleneck for Reasoning Models
Huifeng Yin, Yu Zhao, Minghao Wu +9
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).…
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…
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…