conftrace_

model adaptation

174 papers

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Co-occurring keywords

transfer learning (5449) domain adaptation (4595) parameter-efficient fine-tuning (736) model compression (3302) low-rank adaptation (560) large language model (13587) foundation model (735) automatic speech recognition (1774) knowledge distillation (3725) parameter efficient (173)

Papers

Exploration-Driven Generative Interactive Environments CVPR 2025
Bootstrapping Grounded Chain-of-Thought in Multimodal LLMs for Data-Efficient Model Adaptation ICCV 2025
Time- Memory- and Parameter-Efficient Visual Adaptation CVPR 2024
Parameter Efficient Fine-tuning via Cross Block Orchestration for Segment Anything Model CVPR 2024
ML-SUPERB 2.0: Benchmarking Multilingual Speech Models Across Modeling Constraints, Languages, and Datasets INTERSPEECH 2024
CUNI and LMU Submission to the MRL 2024 Shared Task on Multi-lingual Multi-task Information Retrieval EMNLP 2024
Design Proteins Using Large Language Models: Enhancements and Comparative Analyses ACL 2024
Rethinking Misalignment in Vision-Language Model Adaptation from a Causal Perspective NIPS 2024
LoRA-GA: Low-Rank Adaptation with Gradient Approximation NIPS 2024
AdanCA: Neural Cellular Automata As Adaptors For More Robust Vision Transformer NIPS 2024
MACP: Efficient Model Adaptation for Cooperative Perception WACV 2024
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models CVPR 2024
Universal Semi-Supervised Model Adaptation via Collaborative Consistency Training WACV 2024
V-PETL Bench: A Unified Visual Parameter-Efficient Transfer Learning Benchmark NIPS 2024
Exploring Design Choices for Building Language-Specific LLMs EMNLP 2024
Boosting Image Quality Assessment through Efficient Transformer Adaptation with Local Feature Enhancement CVPR 2024
Model Adaptation for Time Constrained Embodied Control CVPR 2024
PrivAuditor: Benchmarking Data Protection Vulnerabilities in LLM Adaptation Techniques NIPS 2024
Adapters Strike Back CVPR 2024
Synthesize, Partition, then Adapt: Eliciting Diverse Samples from Foundation Models NIPS 2024
TaD: A Plug-and-Play Task-Aware Decoding Method to Better Adapt LLMs on Downstream Tasks IJCAI 2024
Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-Experts NIPS 2024
Multitask Vision-Language Prompt Tuning WACV 2024
Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives NIPS 2024
Enhancing LLM Capabilities Beyond Scaling Up EMNLP 2024