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References (77)

[1]
Fine-Grained VLM Fine-tuning via Latent Hierarchical Adapter Learning
2025Yumiao Zhao, Bo Jiang et al.
[2]
Investigating Redundancy in Multimodal Large Language Models with Multiple Vision Encoders
2025Song Mao, Yang Chen et al.
[3]
Learning to Skip the Middle Layers of Transformers
2025Tim Lawson, Laurence Aitchison
[4]
Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts
2025Debarshi Brahma, Anuska Roy et al.
[5]
Perception Encoder: The best visual embeddings are not at the output of the network
2025Daniel Bolya, Po-Yao Huang et al.
[6]
Logits DeConfusion with CLIP for Few-Shot Learning
2025Shuo Li, Fang Liu et al.
[7]
SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
2025Michael Tschannen, Alexey Gritsenko et al.
[8]
Cross the Gap: Exposing the Intra-modal Misalignment in CLIP via Modality Inversion
2025Marco Mistretta, Alberto Baldrati et al.
[9]
Leveraging the true depth of LLMs
2025Ram'on Calvo Gonz'alez, Daniele Paliotta et al.
[10]
DynaPrompt: Dynamic Test-Time Prompt Tuning
2025Zehao Xiao, Shilin Yan et al.
[11]
Advancing Textual Prompt Learning with Anchored Attributes
2024Zheng Li, Yibing Song et al.
[12]
Prompt as Free Lunch: Enhancing Diversity in Source-Free Cross-domain Few-shot Learning through Semantic-Guided Prompting
2024Linhai Zhuo, Zheng Wang et al.
[13]
Mamba-FSCIL: Dynamic Adaptation with Selective State Space Model for Few-Shot Class-Incremental Learning
2024Xiaojie Li, Yibo Yang et al.
[14]
The Remarkable Robustness of LLMs: Stages of Inference?
2024Vedang Lad, Wes Gurnee et al.
[15]
MMA: Multi-Modal Adapter for Vision-Language Models
2024Lingxiao Yang, Ru-Yuan Zhang et al.
[16]
Low-Rank Few-Shot Adaptation of Vision-Language Models
2024Maxime Zanella, Ismail Ben Ayed
[17]
AMU-Tuning: Effective Logit Bias for CLIP-based Few-shot Learning
2024Yuwei Tang, Zhenyi Lin et al.
[18]
LP++: A Surprisingly Strong Linear Probe for Few-Shot CLIP
2024Yunshi Huang, Fereshteh Shakeri et al.
[19]
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
2024Xin Men, Mingyu Xu et al.
[20]
PromptKD: Unsupervised Prompt Distillation for Vision-Language Models
2024Zheng Li, Xiang Li et al.

Showing 20 of 77 references

Founder's Pitch

"Develop a method to improve Source-Free Cross-Domain Few-Shot Learning by reclaiming underutilized text encoder layers."

Few-Shot LearningScore: 6View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

1/4 signals

2.5

Quick Build

3/4 signals

7.5

Series A Potential

2/4 signals

5

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