Prefix-Tuning: Optimizing Continuous Prompts for Generation
2021/01/01 by Xiang Lisa Li, Percy Liang · 310 citations
Computer Science · #Natural Language Processing Techniques #Speech Recognition and Synthesis #Topic Modeling
paper · pdf · doi:10.18653/v1/2021.acl-long.353
openalex publication_date 2021/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
Abstract
Xiang Lisa Li, Percy Liang. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2021.
Citations
Cited by
- LLMs for Cold-Start Cutting Plane Separator Configuration
- What Changes Can Large-scale Language Models Bring? Intensive Study on\n HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers
- Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
- ConforNets: Latents-Based Conformational Control in OpenFold3
- Learning to Prompt for Vision-Language Models
- Concept Tokens: Learning Behavioral Embeddings Through Concept Definitions
- MISA: Memory-Efficient LLMs Optimization with Module-wise Importance Sampling
- Instant Personalized Large Language Model Adaptation via Hypernetwork
- Zero-Shot Cross-Lingual Transfer using Prefix-Based Adaptation
- Parallel Loop Transformer for Efficient Test-Time Computation Scaling
- zFLoRA: Zero-Latency Fused Low-Rank Adapters
- Calibrating and Rotating: A Unified Framework for Weight Conditioning in PEFT
- DualCap: Enhancing Lightweight Image Captioning via Dual Retrieval with Similar Scenes Visual Prompts
- Kernelized Sparse Fine-Tuning with Bi-level Parameter Competition for Vision Models
- FLoRA: Fused forward-backward adapters for parameter efficient fine-tuning and reducing inference-time latencies of LLMs
- ScaLoRA: Optimally Scaled Low-Rank Adaptation for Efficient High-Rank Fine-Tuning
- VIPAMIN: Visual Prompt Initialization via Embedding Selection and Subspace Expansion
- Adaptive Dual Prompting: Hierarchical Debiasing for Fairness-aware Graph Neural Networks
- Large language model-based task planning for service robots: A review
- Beyond Higher Rank: Token-wise Input-Output Projections for Efficient Low-Rank Adaptation
- Plug-Tagger: A Pluggable Sequence Labeling Framework Using Language Models
- Low-Resource Dialect Adaptation of Large Language Models: A French Dialect Case-Study
- Jarvis: Towards Personalized AI Assistant via Personal KV-Cache Retrieval
- Large Language Models Meet Text-Attributed Graphs: A Survey of Integration Frameworks and Applications
- LLM-Integrated Bayesian State Space Models for Multimodal Time-Series Forecasting
- Compress to Impress: Efficient LLM Adaptation Using a Single Gradient Step on 100 Samples
- Thought Communication in Multiagent Collaboration
- Neural Diversity Regularizes Hallucinations in Small Models
- Hierarchical Sequence Iteration for Heterogeneous Question Answering
- SEMPO: Lightweight Foundation Models for Time Series Forecasting
- Latent Space Factorization in LoRA
- COLA: Continual Learning via Autoencoder Retrieval of Adapters
- Towards Fast LLM Fine-tuning through Zeroth-Order Optimization with Projected Gradient-Aligned Perturbations
- NeuroAda: Activating Each Neuron's Potential for Parameter-Efficient Fine-Tuning
- FedDEAP: Adaptive Dual-Prompt Tuning for Multi-Domain Federated Learning
- ScaleNet: Scaling up Pretrained Neural Networks with Incremental Parameters
- Contextual Attention Modulation: Towards Efficient Multi-Task Adaptation in Large Language Models
- Graph4MM: Weaving Multimodal Learning with Structural Information
- All You Need is One: Capsule Prompt Tuning with a Single Vector
- Exploring Cross-Modal Flows for Few-Shot Learning
- FedHFT: Efficient Federated Finetuning with Heterogeneous Edge Clients
- Knowledge Reasoning Language Model: Unifying Knowledge and Language for Inductive Knowledge Graph Reasoning
- MedREK: Retrieval-Based Editing for Medical LLMs with Key-Aware Prompts
- VisCoP: Visual Probing for Video Domain Adaptation of Vision Language Models
- Data-Model Co-Evolution: Growing Test Sets to Refine LLM Behavior
- Evolution of meta's llama models and parameter-efficient fine-tuning of large language models: a survey
- State Space Prompting via Gathering and Spreading Spatio-Temporal Information for Video Understanding
- QeRL: Beyond Efficiency -- Quantization-enhanced Reinforcement Learning for LLMs
- MeTA-LoRA: Data-Efficient Multi-Task Fine-Tuning for Large Language Models
- CoSPED: Consistent Soft Prompt Targeted Data Extraction and Defense
- In-Context Learning Is Provably Bayesian Inference: A Generalization Theory for Meta-Learning
- MC#: Mixture Compressor for Mixture-of-Experts Large Models
- Long Exposure: Accelerating Parameter-Efficient Fine-Tuning for LLMs under Shadowy Sparsity
- X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model
- StelLA: Subspace Learning in Low-rank Adaptation using Stiefel Manifold
- Doc-to-Atom: Learning to Compile and Compose Memory Atoms
- Parameter-Efficient and Personalized Federated Training of Generative Models at the Edge
- Few-shot multi-token DreamBooth with LoRa for style-consistent character generation
- Multimodal Policy Internalization for Conversational Agents
- D-TPT: Dimensional Entropy Maximization for Calibrating Test-Time Prompt Tuning in Vision-Language Models
- Vision Language Models: A Survey of 26K Papers
- TinyGraphEstimator: Adapting Lightweight Language Models for Graph Structure Inference
- AILoRA: Function-Aware Asymmetric Initialization for Low-Rank Adaptation of Large Language Models
- LadderMoE: Ladder-Side Mixture of Experts Adapters for Bronze Inscription Recognition
- Prompts Generalize with Low Data: Non-vacuous Generalization Bounds for Optimizing Prompts with More Informative Priors
- FlyLoRA: Boosting Task Decoupling and Parameter Efficiency via Implicit Rank-Wise Mixture-of-Experts
- SliceFine: The Universal Winning-Slice Hypothesis for Pretrained Networks
- Post-Norm can Resharpen Attention
- Neologism Learning for Controllability and Self-Verbalization
- Search-R3: Unifying Reasoning and Embedding in Large Language Models
- VA-Adapter: Adapting Ultrasound Foundation Model to Echocardiography Probe Guidance
- Learning to Rewrite Prompts for Bootstrapping LLMs on Downstream Tasks
- When LLMs Can't Help: Real-World Evaluation of LLMs in Nutrition
- Prompt reinforcing for long-term planning of large language models
- AMAQ: Adaptive Mixed-bit Activation Quantization for Collaborative Parameter Efficient Fine-tuning
- MASA: Rethinking the Representational Bottleneck in LoRA with Multi-A Shared Adaptation
- Resource-Efficient Fine-Tuning of LLaMA-3.2-3B for Medical Chain-of-Thought Reasoning
- Beyond the Seen: Bounded Distribution Estimation for Open-Vocabulary Learning
- TiTok: Transfer Token-level Knowledge via Contrastive Excess to Transplant LoRA
- FT-MDT: Extracting Decision Trees from Medical Texts via a Novel Low-rank Adaptation Method
- Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
- FedSRD: Sparsify-Reconstruct-Decompose for Communication-Efficient Federated Large Language Models Fine-Tuning
- C3Editor: Achieving Controllable Consistency in 2D Model for 3D Editing
- Mitigating Forgetting Between Supervised and Reinforcement Learning Yields Stronger Reasoners
- MHA-RAG: Improving Efficiency, Accuracy, and Consistency by Encoding Exemplars as Soft Prompts
- LLM Based Bayesian Optimization for Prompt Search
- Inoculation Prompting: Eliciting traits from LLMs during training can suppress them at test-time
- DoRAN: Stabilizing Weight-Decomposed Low-Rank Adaptation via Noise Injection and Auxiliary Networks
- HoRA: Cross-Head Low-Rank Adaptation with Joint Hypernetworks
- Large Language Models Hallucination: A Comprehensive Survey
- MonitorVLM:A Vision Language Framework for Safety Violation Detection in Mining Operations
- Decoupling Task-Solving and Output Formatting in LLM Generation
- HyperAdaLoRA: Accelerating LoRA Rank Allocation During Training via Hypernetworks without Sacrificing Performance
- GLAI: GreenLightningAI for Accelerated Training through Knowledge Decoupling
- Inclusive Easy-to-Read Generation for Individuals with Cognitive Impairments
- TokMem: Tokenized Procedural Memory for Large Language Models
- Learning a Zeroth-Order Optimizer for Fine-Tuning LLMs
- Retrieval-Augmented Framework for LLM-Based Clinical Decision Support
- Exploring System 1 and 2 communication for latent reasoning in LLMs
- Navigating the Synchrony-Stability Frontier in Adaptive Chatbots
- Efficient Layer-wise LLM Fine-tuning for Revision Intention Prediction
- TAP: Two-Stage Adaptive Personalization of Multi-task and Multi-Modal Foundation Models in Federated Learning
- Adaptive Planning for Multi-Attribute Controllable Summarization with Monte Carlo Tree Search
- Communication-Efficient and Accurate Approach for Aggregation in Federated Low-Rank Adaptation
- RE2: Improving Chinese Grammatical Error Correction via Retrieving Appropriate Examples with Explanation
- Controlled Generation for Private Synthetic Text
- Probing the Limits of Stylistic Alignment in Vision-Language Models
- Rethinking Parameter Sharing for LLM Fine-Tuning with Multiple LoRAs
- FedPOB: Sample-Efficient Federated Prompt Optimization via Bandits
- Prompt and Parameter Co-Optimization for Large Language Models
- Pretraining with hierarchical memories: separating long-tail and common knowledge
- ReasonCACHE: Teaching LLMs To Reason Without Weight Updates
- One-Prompt Strikes Back: Sparse Mixture of Experts for Prompt-based Continual Learning
- GroupCoOp: Group-robust Fine-tuning via Group Prompt Learning
- From Personal to Collective: On the Role of Local and Global Memory in LLM Personalization
- A Hierarchical Structure-Enhanced Personalized Recommendation Model for Traditional Chinese Medicine Formulas Based on KG Diffusion Guidance
- Memory-Efficient Fine-Tuning via Low-Rank Activation Compression
- F-Adapter: Frequency-Adaptive Parameter-Efficient Fine-Tuning in Scientific Machine Learning
- IA2: Alignment with ICL Activations Improves Supervised Fine-Tuning
- Context Parametrization with Compositional Adapters
- Task-Adaptive Parameter-Efficient Fine-Tuning for Weather Foundation Models
- Enhancing Low-Rank Adaptation with Structured Nonlinear Transformations
- Synthetic Dialogue Generation for Interactive Conversational Elicitation & Recommendation (ICER)
- PSRT: Accelerating LRM-based Guard Models via Prefilled Safe Reasoning Traces
- A Tale of Two Experts: Cooperative Learning for Source-Free Unsupervised Domain Adaptation
- PreLoRA: Hybrid Pre-training of Vision Transformers with Full Training and Low-Rank Adapters
- Benchmarking Gaslighting Attacks Against Speech Large Language Models
- Mamba Modulation: On the Length Generalization of Mamba
- Parameter-Efficient Multi-Task Learning via Progressive Task-Specific Adaptation
- TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement
- Tight Sample Complexity for Low-Rank Adaptation: Matching Bounds and Rank Selection
- SkillSmith: Learning to Compose Parametric Skills and Textual Knowledge
- Latent Bridges for Multi-Table Question Answering
- SuperThoughts: Reasoning Tokens in Superposition
- S-GRPO: Unified Post-Training for Large Vision-Language Models
- CLIP-Adapter: Better Vision-Language Models with Feature Adapters
- Basecalling for DNA Storage
- Unseen Speaker and Language Adaptation for Lightweight Text-To-Speech with Adapters
- Previously on... Automating Code Review
- Riemannian Optimization for LoRA on the Stiefel Manifold
- An Explanation of In-context Learning as Implicit Bayesian Inference
- CompLLM: Compression for Long Context Q&A
- Memory in Large Language Models: Mechanisms, Evaluation and Evolution
- HyperAdapt: Simple High-Rank Adaptation
- Advances in Large Language Models for Medicine
- Accurate and Efficient Low-Rank Model Merging in Core Space
- Dynamic Embedding of Hierarchical Visual Features for Efficient Vision-Language Fine-Tuning
- TASO: Task-Aligned Sparse Optimization for Parameter-Efficient Model Adaptation
- QWHA: Quantization-Aware Walsh-Hadamard Adaptation for Parameter-Efficient Fine-Tuning on Large Language Models
- Difficulty-Aware Score Generation for Piano Sight-Reading
- Dynamic Expert Specialization: Towards Catastrophic Forgetting-Free Multi-Domain MoE Adaptation
- Domain-Adaptive Pre-Training for Arabic Aspect-Based Sentiment Analysis: A Comparative Study of Domain Adaptation and Fine-Tuning Strategies
- Federated Learning with Ad-hoc Adapter Insertions: The Case of Soft-Embeddings for Training Classifier-as-Retriever
- BEFT: Bias-Efficient Fine-Tuning of Language Models
- CBPNet: A Continual Backpropagation Prompt Network for Alleviating Plasticity Loss on Edge Devices
- Continuous Entailment Patterns for Lexical Inference in Context
- Adaptive LoRA Experts Allocation and Selection for Federated Fine-Tuning
- PILOT: Steering Synthetic Data Generation with Psychological & Linguistic Output Targeting
- Lost in Translation? Vocabulary Alignment for Source-Free Adaptation in Open-Vocabulary Semantic Segmentation
- DF-LLaVA: Unlocking MLLMs for Synthetic Image Detection via Knowledge Injection and Conflict-Driven Self-Reflection
- Exploring Data and Parameter Efficient Strategies for Arabic Dialect Identifications
- An LLM-based multi-agent framework for agile effort estimation
- DropLoRA: Sparse Low-Rank Adaptation for Parameter-Efficient Fine-Tuning
- A Systematic Evaluation of Parameter-Efficient Fine-Tuning Methods for the Security of Code LLMs
- MEJO: MLLM-Engaged Surgical Triplet Recognition via Inter- and Intra-Task Joint Optimization
- Towards Alignment-Centric Paradigm: A Survey of Instruction Tuning in Large Language Models
- CBP-Tuning: Efficient Local Customization for Black-box Large Language Models
- Context-Aware Language Models for Forecasting Market Impact from Sequences of Financial News
- MAPGD: Multi-Agent Prompt Gradient Descent for Collaborative Prompt Optimization
- Learned Structure in Cartridges: Keys as Shareable Routers in Self-Studied Representations
- CrunchLLM: Multitask LLMs for Structured Business Reasoning and Outcome Prediction
- Contrastive Prompt Clustering for Weakly Supervised Semantic Segmentation
- Sensitivity-LoRA: Low-Load Sensitivity-Based Fine-Tuning for Large Language Models
- CrossPT: Exploring Cross-Task Transferability through Multi-Task Prompt Tuning
- Fine-Tuning Vision-Language Models for Visual Navigation Assistance
- From Detection to Mitigation: Addressing Gender Bias in Chinese Texts via Efficient Tuning and Voting-Based Rebalancing
- AI-driven Remote Facial Skin Hydration and TEWL Assessment from Selfie Images: A Systematic Solution
- Towards Meta-Cognitive Knowledge Editing for Multimodal LLMs
- L1RA: Dynamic Rank Assignment in LoRA Fine-Tuning
- Manipulating Transformer-Based Models: Controllability, Steerability, and Robust Interventions
- Characterizing Fitness Landscape Structures in Prompt Engineering
- Modular Embedding Recomposition for Incremental Learning
- Towards a Unified View of Parameter-Efficient Transfer Learning
- Singular Value Few-shot Adaptation of Vision-Language Models
- Comparison of End-to-end Speech Assessment Models for the NOCASA 2025 Challenge
- Structure-Learnable Adapter Fine-Tuning for Parameter-Efficient Large Language Models
- On the Evolution of Federated Post-Training Large Language Models: A Model Accessibility View
- Better by Comparison: Retrieval-Augmented Contrastive Reasoning for Automatic Prompt Optimization
- LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents
- VaccineRAG: Boosting Multimodal Large Language Models' Immunity to Harmful RAG Samples
- Extracting OPQRST in Electronic Health Records using Large Language Models with Reasoning
- GEM: A Scale-Aware and Distribution-Sensitive Sparse Fine-Tuning Framework for Effective Downstream Adaptation
- GradES: Significantly Faster Training in Transformers with Gradient-Based Early Stopping
- Reasoning Vectors: Transferring Chain-of-Thought Capabilities via Task Arithmetic
- FediLoRA: Practical Federated Fine-Tuning of Foundation Models Under Missing-Modality Constraints
- Towards Open-World Retrieval-Augmented Generation on Knowledge Graph: A Multi-Agent Collaboration Framework
- Integrating Time Series into LLMs via Multi-layer Steerable Embedding Fusion for Enhanced Forecasting
- MEPT: Mixture of Expert Prompt Tuning as a Manifold Mapper
- Discrete Prompt Tuning via Recursive Utilization of Black-box Multimodal Large Language Model for Personalized Visual Emotion Recognition
- Memory Limitations of Prompt Tuning in Transformers
- Adaptive Point-Prompt Tuning: Fine-Tuning Heterogeneous Foundation Models for 3D Point Cloud Analysis
- Not All Parameters Are Created Equal: Smart Isolation Boosts Fine-Tuning Performance
- FedReFT: Federated Representation Fine-Tuning with All-But-Me Aggregation
- TokenVerse++: Towards Flexible Multitask Learning with Dynamic Task Activation
- Reflection-Enhanced Meta-Optimization Integrating TextGrad-style Prompt Optimization with Memory-Driven Self-Evolution
- Latent Self-Consistency for Reliable Majority-Set Selection in Short- and Long-Answer Reasoning
- Type-Compliant Adaptation Cascades: Adapting Programmatic LM Workflows to Data
- Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection
- J6: Jacobian-Driven Role Attribution for Multi-Objective Prompt Optimization in LLMs
- Cross-Prompt Encoder for Low-Performing Languages
- Decentralized Rank Scheduling for Energy-Constrained Multi-Task Federated Fine-Tuning in Edge-Assisted IoV Networks
- APIO: Automatic Prompt Induction and Optimization for Grammatical Error Correction and Text Simplification
- Magical: Medical Lay Language Generation via Semantic Invariance and Layperson-tailored Adaptation
- Classifier Language Models: Unifying Sparse Finetuning and Adaptive Tokenization for Specialized Classification Tasks
- DeCAL Tokenwise Compression
- Dual Information Speech Language Models for Emotional Conversations
- DCoAR: Deep Concept Injection into Unified Autoregressive Models for Personalized Text-to-Image Generation
- BoRA: Towards More Expressive Low-Rank Adaptation with Block Diversity
- PREF: Reference-Free Evaluation of Personalised Text Generation in LLMs
- PRvL: Quantifying the Capabilities and Risks of Large Language Models for PII Redaction
- Optimal Corpus Aware Training for Neural Machine Translation
- BEE-RAG: Balanced Entropy Engineering for Retrieval-Augmented Generation
- ETTA: Efficient Test-Time Adaptation for Vision-Language Models through Dynamic Embedding Updates
- Zero-Residual Concept Erasure via Progressive Alignment in Text-to-Image Model
- Continual Learning for VLMs: A Survey and Taxonomy Beyond Forgetting
- DTPA: Dynamic Token-level Prefix Augmentation for Controllable Text Generation
- Dual Prompt Learning for Adapting Vision-Language Models to Downstream Image-Text Retrieval
- Tensorized Clustered LoRA Merging for Multi-Task Interference
- Efficient Morphology-Aware Policy Transfer to New Embodiments
- EmbedGrad: Gradient-Based Prompt Optimization in Embedding Space for Large Language Models
- Variety Is the Spice of Life: Detecting Misinformation with Dynamic Environmental Representations
- MoKA: Mixture of Kronecker Adapters
- Can LLMs Generate High-Quality Task-Specific Conversations?
- Kron-LoRA: Hybrid Kronecker-LoRA Adapters for Scalable, Sustainable Fine-tuning
- Model Recycling Framework for Multi-Source Data-Free Supervised Transfer Learning
- Harnessing Textual Semantic Priors for Knowledge Transfer and Refinement in CLIP-Driven Continual Learning
- Adaptive Content Restriction for Large Language Models via Suffix Optimization
- Zero-Shot Anomaly Detection with Dual-Branch Prompt Selection
- P3: Prompts Promote Prompting
- RainbowPrompt: Diversity-Enhanced Prompt-Evolving for Continual Learning
- FaceGCD: Generalized Face Discovery via Dynamic Prefix Generation
- Learning to Imitate with Less: Efficient Individual Behavior Modeling in Chess
- Regularizing Subspace Redundancy of Low-Rank Adaptation
- AF-CLIP: Zero-Shot Anomaly Detection via Anomaly-Focused CLIP Adaptation
- Cross-Domain Few-Shot Learning with Coalescent Projections and Latent Space Reservation
- CLoRA: Parameter-Efficient Continual Learning with Low-Rank Adaptation
- OW-CLIP: Data-Efficient Visual Supervision for Open-World Object Detection via Human-AI Collaboration
- MOCHA: Are Code Language Models Robust Against Multi-Turn Malicious Coding Prompts?
- Mining Contextualized Visual Associations from Images for Creativity Understanding
- IntentVCNet: Bridging Spatio-Temporal Gaps for Intention-Oriented Controllable Video Captioning
- Decoupling Knowledge and Reasoning in LLMs: An Exploration Using Cognitive Dual-System Theory
- StyleAdaptedLM: Enhancing Instruction Following Models with Efficient Stylistic Transfer
- E.A.R.T.H.: Structuring Creative Evolution through Model Error in Generative AI
- Deep Generative Models in Condition and Structural Health Monitoring: Opportunities, Limitations and Future Outlook
- Hierarchical Cross-modal Prompt Learning for Vision-Language Models
- Privacy Risks of LLM-Empowered Recommender Systems: An Inversion Attack Perspective
- MambAdapter: Lightweight Mamba-Based Adapters for Parameter-Efficient Transfer Learning in Speech and Audio
- Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories
- GRID: Scalable Task-Agnostic Prompt-Based Continual Learning for Language Models
- FedDPG: An Adaptive Yet Efficient Prompt-tuning Approach in Federated Learning Settings
- Automating Steering for Safe Multimodal Large Language Models
- Promptomatix: An Automatic Prompt Optimization Framework for Large Language Models
- DiffOSeg: Omni Medical Image Segmentation via Multi-Expert Collaboration Diffusion Model
- PROL : Rehearsal Free Continual Learning in Streaming Data via Prompt Online Learning
- Modeling Code: Is Text All You Need?
- Graph World Model
- MixLoRA-DSI: Dynamically Expandable Mixture-of-LoRA Experts for Rehearsal-Free Generative Retrieval over Dynamic Corpora
- Stabilizing Black-Box Prompt Optimization with Textual Regularization and Signal Aggregation
- Mechanistic Interpretability of LoRA-Adapted Language Models for Nuclear Reactor Safety Applications
- CKAA: Cross-subspace Knowledge Alignment and Aggregation for Robust Continual Learning
- SynBridge: Bridging Reaction States via Discrete Flow for Bidirectional Reaction Prediction
- Low-rank Momentum Factorization for Memory Efficient Training
- Defending Against Prompt Injection With a Few DefensiveTokens
- Beyond the Linear Separability Ceiling: Aligning Representations in VLMs
- HGMP:Heterogeneous Graph Multi-Task Prompt Learning
- Bridging the Plausibility-Validity Gap by Fine-Tuning a Reasoning-Enhanced LLM for Chemical Synthesis and Discovery
- Mask6D: Masked Pose Priors For 6D Object Pose Estimation
- Weighted Multi-Prompt Learning with Description-free Large Language Model Distillation
- A Survey on Prompt Tuning
- AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework
- LoRA-Augmented Generation (LAG) for Knowledge-Intensive Language Tasks
- pFedMMA: Personalized Federated Fine-Tuning with Multi-Modal Adapter for Vision-Language Models
- Dual Modality-Aware Gated Prompt Tuning for Few-Shot Multimodal Sarcasm Detection
- LoRA Is Slower Than You Think
- Context Tuning for In-Context Optimization
- ESSA: Evolutionary Strategies for Scalable Alignment
- PromptSR: Cascade Prompting for Lightweight Image Super-Resolution
- Animation Needs Attention: A Holistic Approach to Slides Animation Comprehension with Visual-Language Models
- Open-Vocabulary Object Detection in UAV Imagery: A Review and Future Perspectives
- MemOS: A Memory OS for AI System
- DoMIX: An Efficient Framework for Exploiting Domain Knowledge in Fine-Tuning
- Emotionally Intelligent Task-oriented Dialogue Systems: Architecture, Representation, and Optimisation
- EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices
- Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages
- Modeling Data Diversity for Joint Instance and Verbalizer Selection in Cold-Start Scenarios
- Impact of Fine-Tuning Methods on Memorization in Large Language Models
- A Closer Look at Conditional Prompt Tuning for Vision-Language Models
- Less Data, More Security: Advancing Cybersecurity LLMs Specialization via Resource-Efficient Domain-Adaptive Continuous Pre-training with Minimal Tokens
- MedSAM-CA: A CNN-Augmented ViT with Attention-Enhanced Multi-Scale Fusion for Medical Image Segmentation
- Cell2Sentence: Teaching Large Language Models the Language of Biology
- FinStat2SQL: A Text2SQL Pipeline for Financial Statement Analysis
- VisualPrompter: Prompt Optimization with Visual Feedback for Text-to-Image Synthesis
- Integrating Large Language Models in Financial Investments and Market Analysis: A Survey
- Mettle: Meta-Token Learning for Memory-Efficient Audio-Visual Adaptation
- Attention to the Burstiness in Visual Prompt Tuning!
- ReasonBridge: Efficient Reasoning Transfer from Closed to Open-Source Language Models
- Projected Compression: Trainable Projection for Efficient Transformer Compression
- FoGE: Fock Space inspired encoding for graph prompting
- Exploring Adapter Design Tradeoffs for Low Resource Music Generation
- Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models
Related