Search Results for author: Junjie Guo

Found 6 papers, 2 papers with code

Extroversion or Introversion? Controlling The Personality of Your Large Language Models

1 code implementation7 Jun 2024 Yanquan Chen, Zhen Wu, Junjie Guo, ShuJian Huang, Xinyu Dai

Our investigation revealed a hierarchy of effectiveness in control: Prompt > SFT > RLHF > Continual Pre-train.

Text Generation

AlignGPT: Multi-modal Large Language Models with Adaptive Alignment Capability

no code implementations23 May 2024 Fei Zhao, Taotian Pang, Chunhui Li, Zhen Wu, Junjie Guo, Shangyu Xing, Xinyu Dai

In the pre-training stage, instead of treating all image-text pairs equally, we assign different levels of alignment capabilities to different image-text pairs.

Language Modelling Large Language Model +1

Emotion-Anchored Contrastive Learning Framework for Emotion Recognition in Conversation

1 code implementation29 Mar 2024 Fangxu Yu, Junjie Guo, Zhen Wu, Xinyu Dai

To achieve this, we utilize label encodings as anchors to guide the learning of utterance representations and design an auxiliary loss to ensure the effective separation of anchors for similar emotions.

Contrastive Learning Emotion Recognition in Conversation

DAMSDet: Dynamic Adaptive Multispectral Detection Transformer with Competitive Query Selection and Adaptive Feature Fusion

no code implementations1 Mar 2024 Junjie Guo, Chenqiang Gao, Fangcen Liu, Deyu Meng, Xinbo Gao

To effectively mine the complementary information and adapt to misalignment situations, we propose a Multispectral Deformable Cross-attention module to adaptively sample and aggregate multi-semantic level features of infrared and visible images for each object.

Object object-detection +1

InfMAE: A Foundation Model in Infrared Modality

no code implementations1 Feb 2024 Fangcen Liu, Chenqiang Gao, Yaming Zhang, Junjie Guo, Jinhao Wang, Deyu Meng

Finally, based on the fact that infrared images do not have a lot of details and texture information, we design an infrared decoder module, which further improves the performance of downstream tasks.

Decoder Self-Supervised Learning

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