481 citations · 1.2k across the 21 of their papers we have counts for
6 papers · 1 filter
MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning
Ke Wang, Houxing Ren, Aojun Zhou +7
The recently released GPT-4 Code Interpreter has demonstrated remarkable proficiency in solving challenging math problems, primarily attributed to its ability to seamlessly reason…
Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification
Aojun Zhou, Ke Wang, Zimu Lu +8
Recent progress in large language models (LLMs) like GPT-4 and PaLM-2 has brought significant advancements in addressing math reasoning problems. In particular, OpenAI's latest ver…
JourneyDB: A Benchmark for Generative Image Understanding
Keqiang Sun, Junting Pan, Yuying Ge +11
While recent advancements in vision-language models have had a transformative impact on multi-modal comprehension, the extent to which these models possess the ability to comprehen…
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
Peng Gao, Jiaming Han, Renrui Zhang +9
How to efficiently transform large language models (LLMs) into instruction followers is recently a popular research direction, while training LLM for multi-modal reasoning remains…
FeatAug-DETR: Enriching One-to-Many Matching for DETRs with Feature Augmentation
Rongyao Fang, Peng Gao, Aojun Zhou +4
One-to-one matching is a crucial design in DETR-like object detection frameworks. It enables the DETR to perform end-to-end detection. However, it also faces challenges of lacking…
LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention
Renrui Zhang, Jiaming Han, Chris Liu +7
We present LLaMA-Adapter, a lightweight adaption method to efficiently fine-tune LLaMA into an instruction-following model. Using 52K self-instruct demonstrations, LLaMA-Adapter on…