most citedTowards Achieving Human Parity on End-to-end Simultaneous Speech Translation via LLM Agent

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2025

CrowdAgent: Multi-Agent Managed Multi-Source Annotation System

Maosheng Qin, Renyu Zhu, Mingxuan Xia +8

High-quality annotated data is a cornerstone of modern Natural Language Processing (NLP). While recent methods begin to leverage diverse annotation sources-including Large Language…

cs.SE20251 cited

AetherCode: Evaluating LLMs' Ability to Win In Premier Programming Competitions

Zihan Wang, Jiaze Chen, Zhicheng Liu +25

Competitive programming has emerged as a critical benchmark for evaluating the reasoning and coding capabilities of Large Language Models (LLMs). Despite impressive progress on exi…

cs.CL2025

Seed-X: Building Strong Multilingual Translation LLM with 7B Parameters

Shanbo Cheng, Yu Bao, Qian Cao +23

Multilingual translation stands as a challenging task for large language models (LLMs) to handle intricate language patterns and stilted translations that arise in automated transl…

cs.LG2025

DuPO: Enabling Reliable LLM Self-Verification via Dual Preference Optimization

Shuaijie She, Yu Bao, Yu Lu +7

We present DuPO, a dual learning-based preference optimization framework that generates annotation-free feedback via a generalized duality. DuPO addresses two key limitations: Rein…

cs.CL2025

Seed LiveInterpret 2.0: End-to-end Simultaneous Speech-to-speech Translation with Your Voice

Shanbo Cheng, Yu Bao, Zhichao Huang +25

Simultaneous Interpretation (SI) represents one of the most daunting frontiers in the translation industry, with product-level automatic systems long plagued by intractable challen…

cs.CL2025

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition

Tianduo Wang, Lu Xu, Wei Lu +1

Recent advances in Automatic Speech Recognition (ASR) have been largely fueled by massive speech corpora. However, extending coverage to diverse languages with limited resources re…