1 citations · 2 across the 11 of their papers we have counts for
12 papers
Inject, Align, Recover: Staged Post-Training for Retrieval-Free Document Knowledge Internalization
Qian Kou, Xiaofeng Shi, Xiaosong Qiu +1
Large language models often fail to answer questions about a bounded document collection when the source documents are not retrieved at inference time. We study this setting as doc…
Wnuan: Staged Post-Training for Question Answering over Proprietary Enterprise Knowledge
Xiaofeng Shi, Xiaosong Qiu, Wenxin Ma +6
Enterprise question answering requires models to acquire proprietary knowledge without discarding general capabilities. We present Wnuan, a three-stage pipeline that constructs tas…
ChartWalker: Benchmarking the Cross-Chart RAG Task with Hierarchical Knowledge Graphs
Ning Tang, Chenghan Xie, Hanyang Yuan +6
Cross-Chart Retrieval-Augmented Generation (RAG) is critical for complex multi-modal analytical tasks in scientific, business, and political domains. However, existing benchmarks e…
RAFT: Data Refinement and Adaptive Distillation for Domain Fine-Tuning with Alleviated Forgetting
Yuduo Li, Xiaofeng Shi, Qian Kou +2
Domain-specific supervised fine-tuning (SFT) often improves in-domain performance at the cost of degrading a model's general capabilities. We view this degradation through two prac…
MechVQA: Benchmarking and Enhancing Multimodal LLMs on Comprehensive Mechanical Drawing Understanding
Qian Kou, Xiaofeng Shi, Yulin Li +4
Multimodal Large Language Models (MLLMs) have demonstrated significant achievements in general visual question answering (VQA) tasks. However, they remain brittle on mechanical eng…
Rethinking Supervised Fine-Tuning: Emphasizing Key Answer Tokens for Improved LLM Accuracy
Xiaofeng Shi, Qian Kou, Yuduo Li +1
With the rapid advancement of Large Language Models (LLMs), the Chain-of-Thought (CoT) component has become significant for complex reasoning tasks. However, in conventional Superv…
SPAR: Scholar Paper Retrieval with LLM-based Agents for Enhanced Academic Search
Xiaofeng Shi, Yuduo Li, Qian Kou +3
Recent advances in large language models (LLMs) have opened new opportunities for academic literature retrieval. However, existing systems often rely on rigid pipelines and exhibit…
SciSage: A Multi-Agent Framework for High-Quality Scientific Survey Generation
Xiaofeng Shi, Qian Kou, Yuduo Li +5
The rapid growth of scientific literature demands robust tools for automated survey-generation. However, current large language model (LLM)-based methods often lack in-depth analys…
CareBot: A Pioneering Full-Process Open-Source Medical Language Model
Lulu Zhao, Weihao Zeng, Xiaofeng Shi +1
Recently, both closed-source LLMs and open-source communities have made significant strides, outperforming humans in various general domains. However, their performance in specific…
MoSLD: An Extremely Parameter-Efficient Mixture-of-Shared LoRAs for Multi-Task Learning
Lulu Zhao, Weihao Zeng, Xiaofeng Shi +1
Recently, LoRA has emerged as a crucial technique for fine-tuning large pre-trained models, yet its performance in multi-task learning scenarios often falls short. In contrast, the…
CCI3.0-HQ: a large-scale Chinese dataset of high quality designed for pre-training large language models
Liangdong Wang, Bo-Wen Zhang, Chengwei Wu +7
We present CCI3.0-HQ (https://huggingface.co/datasets/BAAI/CCI3-HQ), a high-quality 500GB subset of the Chinese Corpora Internet 3.0 (CCI3.0)(https://huggingface.co/datasets/BAAI/C…
Aqulia-Med LLM: Pioneering Full-Process Open-Source Medical Language Models
Lulu Zhao, Weihao Zeng, Xiaofeng Shi +3
Recently, both closed-source LLMs and open-source communities have made significant strides, outperforming humans in various general domains. However, their performance in specific…