{"total":26,"rows":[{"id":"2404.03592","title":"ReFT: Representation Finetuning for Language Models","created":"2024-04-04","cited_by_count":197,"area":null},{"id":"2406.09044","title":"MiLoRA: Harnessing Minor Singular Components for Parameter-Efficient LLM Finetuning","created":"2024-06-13","cited_by_count":94,"area":null},{"id":"2406.01563","title":"LoFiT: Localized Fine-tuning on LLM Representations","created":"2024-06-03","cited_by_count":57,"area":null},{"id":"2505.20154","title":"UORA: Uniform Orthogonal Reinitialization Adaptation in Parameter-Efficient Fine-Tuning of Large Models","created":"2025-05-26","cited_by_count":11,"area":null},{"id":"2409.00119","title":"3-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability","created":"2024-08-28","cited_by_count":10,"area":null},{"id":"2503.18225","title":"DeLoRA: Decoupling Angles and Strength in Low-rank Adaptation","created":"2025-03-23","cited_by_count":10,"area":null},{"id":"2406.10976","title":"Promoting Data and Model Privacy in Federated Learning through Quantized LoRA","created":"2024-06-16","cited_by_count":8,"area":null},{"id":"2410.01870","title":"PEANuT: Parameter-Efficient Adaptation with Weight-aware Neural Tweakers","created":"2024-10-02","cited_by_count":8,"area":null},{"id":"2502.01179","title":"Joint Localization and Activation Editing for Low-Resource Fine-Tuning","created":"2025-02-03","cited_by_count":8,"area":null},{"id":"2505.11235","title":"Efficient Orthogonal Fine-Tuning with Principal Subspace Adaptation","created":"2025-05-16","cited_by_count":4,"area":null},{"id":"2505.23808","title":"DenseLoRA: Dense Low-Rank Adaptation of Large Language Models","created":"2025-05-27","cited_by_count":4,"area":null},{"id":"2506.06686","title":"Learning Distribution-Wise Control in Representation Space for Language Models","created":"2025-06-07","cited_by_count":4,"area":null},{"id":"2409.16913","title":"Tell Me What You Don't Know: Enhancing Refusal Capabilities of Role-Playing Agents via Representation Space Analysis and Editing","created":"2024-09-25","cited_by_count":3,"area":null},{"id":"2510.21834","title":"Restoring Pruned Large Language Models via Lost Component Compensation","created":"2025-10-22","cited_by_count":3,"area":null},{"id":"2410.12130","title":"Iter-AHMCL: Alleviate Hallucination for Large Language Model via Iterative Model-level Contrastive Learning","created":"2024-10-16","cited_by_count":2,"area":null},{"id":"2503.10617","title":"Compositional Subspace Representation Fine-tuning for Adaptive Large Language Models","created":"2025-03-13","cited_by_count":2,"area":null},{"id":"2510.12121","title":"Precise Attribute Intensity Control in Large Language Models via Targeted Representation Editing","created":"2025-10-14","cited_by_count":2,"area":null},{"id":"2507.10855","title":"Sparse Fine-Tuning of Transformers for Generative Tasks","created":"2025-07-14","cited_by_count":1,"area":null},{"id":"2509.15974","title":"BEFT: Bias-Efficient Fine-Tuning of Language Models in Low-Data Regimes","created":"2025-09-19","cited_by_count":1,"area":null},{"id":"2510.18940","title":"NeuroAda: Activating Each Neuron's Potential for Parameter-Efficient Fine-Tuning","created":"2025-10-21","cited_by_count":0,"area":null},{"id":"2512.04296","title":"GRASP: GRouped Activation Shared Parameterization for Parameter-Efficient Fine-Tuning and Robust Inference of Transformers","created":"2025-12-03","cited_by_count":0,"area":null},{"id":"2604.11841","title":"Polynomial Expansion Rank Adaptation: Enhancing Low-Rank Fine-Tuning with High-Order Interactions","created":"2026-04-12","cited_by_count":0,"area":null},{"id":"2606.10706","title":"Unifying Data, Memory, and Compute Efficiency in LLM training: A Survey","created":"2026-06-09","cited_by_count":0,"area":null},{"id":"2606.15416","title":"Encode Errors: Representational Retrieval of In-Context Demonstrations for Multilingual Grammatical Error Correction","created":"2026-06-13","cited_by_count":0,"area":null},{"id":"2609.23979","title":"AURA: Uncertainty-Routed Activation Editing for Acoustic Grounding in Speech Foundation Models","created":"2026-09-21","cited_by_count":0,"area":null},{"id":"2610.00928","title":"Efficient Task Adaptation in Large Language Models: A Survey of Weight-Based, Prompt-Based, and Embedding-Based Adaptations","created":"2026-10-01","cited_by_count":0,"area":null}],"next_cursor":null}