25 citations · 41 across the 10 of their papers we have counts for
12 papers
PremiseCheck: Efficient Fact-Checking of Human and AI Peer Reviews
Dingjie Song, Zhiling Yan, Ziqian Zhang +2
Peer review is under strain from the growth of submissions, and review comments written by humans or AI can misstate what a paper says. We introduce ReviewFact, a benchmark that la…
LEV: Thinking Fast and Deep with Looped Decision Models
Dingjie Song, Zhiling Yan, Yuxuan Zhang +1
Decision models answer typed questions about an input with one probability per option, computed in a single forward pass without generating text. Like the fast System 1 of dual-pro…
BlenderLLM: Training Large Language Models for Computer-Aided Design with Self-improvement
Yuhao Du, Shunian Chen, Wenbo Zan +6
The application of Large Language Models (LLMs) in Computer-Aided Design (CAD) remains an underexplored area, despite their remarkable advancements in other domains. In this paper,…
Exploring Compositional Generalization of Multimodal LLMs for Medical Imaging
Zhenyang Cai, Junying Chen, Rongsheng Wang +6
Medical imaging provides essential visual insights for diagnosis, and multimodal large language models (MLLMs) are increasingly utilized for its analysis due to their strong genera…
Both Text and Images Leaked! A Systematic Analysis of Data Contamination in Multimodal LLM
Dingjie Song, Sicheng Lai, Mingxuan Wang +3
The rapid advancement of multimodal large language models (MLLMs) has significantly enhanced performance across benchmarks. However, data contamination-unintentional memorization o…
LongLLaVA: Scaling Multi-modal LLMs to 1000 Images Efficiently via a Hybrid Architecture
Xidong Wang, Dingjie Song, Shunian Chen +5
Expanding the long-context capabilities of Multi-modal Large Language Models~(MLLMs) is critical for advancing video understanding and high-resolution image analysis. Achieving thi…
MileBench: Benchmarking MLLMs in Long Context
Dingjie Song, Shunian Chen, Guiming Hardy Chen +3
Despite the advancements and impressive performance of Multimodal Large Language Models (MLLMs) on benchmarks, their effectiveness in real-world, long-context, and multi-image task…
HuatuoGPT-II, One-stage Training for Medical Adaption of LLMs
Junying Chen, Xidong Wang, Ke Ji +11
Adapting a language model into a specific domain, a.k.a `domain adaption', is a common practice when specialized knowledge, e.g. medicine, is not encapsulated in a general language…
AceGPT, Localizing Large Language Models in Arabic
Huang Huang, Fei Yu, Jianqing Zhu +17
This paper is devoted to the development of a localized Large Language Model (LLM) specifically for Arabic, a language imbued with unique cultural characteristics inadequately addr…
CMB: A Comprehensive Medical Benchmark in Chinese
Xidong Wang, Guiming Hardy Chen, Dingjie Song +8
Large Language Models (LLMs) provide a possibility to make a great breakthrough in medicine. The establishment of a standardized medical benchmark becomes a fundamental cornerstone…
TCBERT: A Technical Report for Chinese Topic Classification BERT
Ting Han, Kunhao Pan, Xinyu Chen +5
Bidirectional Encoder Representations from Transformers or BERT~\cite{devlin-etal-2019-bert} has been one of the base models for various NLP tasks due to its remarkable performance…
R3: A Reading Comprehension Benchmark Requiring Reasoning Processes
Ran Wang, Kun Tao, Dingjie Song +4
Existing question answering systems can only predict answers without explicit reasoning processes, which hinder their explainability and make us overestimate their ability of under…