47 citations · 51 across the 10 of their papers we have counts for
10 papers
Dejavu: Towards Experience Feedback Learning for Embodied Intelligence
Shaokai Wu, Yanbiao Ji, Qiuchang Li +7
Embodied agents face a fundamental limitation: once deployed in real-world environments, they cannot easily acquire new knowledge to improve task performance. In this paper, we pro…
An Efficient, Reliable and Observable Collective Communication Library in Large-scale GPU Training Clusters
Mingjun Zhang, Xiaohe Hu, Menghao Zhang +21
Large-scale LLM training requires collective communication libraries to exchange data among distributed GPUs. As a company dedicated to building and operating large-scale GPU train…
Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models
Bilge Taskin, Wenxiong Xie, Teddy Lazebnik
Symbolic regression (SR) has emerged as a powerful tool for automated scientific discovery, enabling the derivation of governing equations from experimental data. A growing body of…
Prompting a Weighting Mechanism into LLM-as-a-Judge in Two-Step: A Case Study
Wenwen Xie, Gray Gwizdz, Dongji Feng
While Large Language Models (LLMs) have emerged as promising tools for evaluating Natural Language Generation (NLG) tasks, their effectiveness is limited by their inability to appr…
Yi-Lightning Technical Report
Alan Wake, Bei Chen, C. X. Lv +41
This technical report presents Yi-Lightning, our latest flagship large language model (LLM). It achieves exceptional performance, ranking 6th overall on Chatbot Arena, with particu…
MathLearner: A Large Language Model Agent Framework for Learning to Solve Mathematical Problems
Wenbei Xie, Donglin Liu, Haoran Yan +2
With the development of artificial intelligence (AI), large language models (LLM) are widely used in many fields. However, the reasoning ability of LLM is still very limited when i…
ENOVA: Autoscaling towards Cost-effective and Stable Serverless LLM Serving
Tao Huang, Pengfei Chen, Kyoka Gong +5
Since the increasing popularity of large language model (LLM) backend systems, it is common and necessary to deploy stable serverless serving of LLM on multi-GPU clusters with auto…
How Out-of-Distribution Detection Learning Theory Enhances Transformer: Learnability and Reliability
Yijin Zhou, Yutang Ge, Wenyuan Xie +3
Transformers excel in natural language processing and computer vision tasks. However, they still face challenges in generalizing to Out-of-Distribution (OOD) datasets, i.e. data wh…
Yi: Open Foundation Models by 01.AI
01. AI, :, Alex Young +30
We introduce the Yi model family, a series of language and multimodal models that demonstrate strong multi-dimensional capabilities. The Yi model family is based on 6B and 34B pret…
Analysis of the Reasoning with Redundant Information Provided Ability of Large Language Models
Wenbei Xie
Recent advancements in Large Language Models (LLMs) have demonstrated impressive capabilities across a range of natural language processing tasks, especially in reasoning, a corner…