{"total":115,"rows":[{"id":"2510.10274","title":"X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model","created":"2025-10-11","cited_by_count":303,"area":"vla"},{"id":"2404.02948","title":"PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models","created":"2024-04-03","cited_by_count":269,"area":null},{"id":"2305.11554","title":"ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings","created":"2023-05-19","cited_by_count":240,"area":"agents"},{"id":"2310.16427","title":"PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization","created":"2023-10-25","cited_by_count":233,"area":null},{"id":"2312.12148","title":"Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment","created":"2023-12-19","cited_by_count":230,"area":null},{"id":"2312.03863","title":"Efficient Large Language Models: A Survey","created":"2023-12-06","cited_by_count":186,"area":null},{"id":"2404.15159","title":"MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts","created":"2024-04-22","cited_by_count":147,"area":"moe"},{"id":"2310.04988","title":"The Troubling Emergence of Hallucination in Large Language Models -- An Extensive Definition, Quantification, and Prescriptive Remediations","created":"2023-10-08","cited_by_count":131,"area":null},{"id":"2306.13090","title":"PromptIR: Prompting for All-in-One Blind Image Restoration","created":"2023-06-22","cited_by_count":114,"area":null},{"id":"2310.03270","title":"EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models","created":"2023-10-05","cited_by_count":78,"area":"diffusion"},{"id":"2310.08184","title":"Learning from models beyond fine-tuning","created":"2023-10-12","cited_by_count":48,"area":null},{"id":"2311.16926","title":"LLaFS: When Large Language Models Meet Few-Shot Segmentation","created":"2023-11-28","cited_by_count":48,"area":null},{"id":"2410.19878","title":"Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies","created":"2024-10-24","cited_by_count":47,"area":null},{"id":"2310.19698","title":"When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations","created":"2023-10-30","cited_by_count":43,"area":null},{"id":"2407.15720","title":"Do Large Language Models Have Compositional Ability? An Investigation into Limitations and Scalability","created":"2024-07-22","cited_by_count":40,"area":null},{"id":"2402.15179","title":"Advancing Parameter Efficiency in Fine-tuning via Representation Editing","created":"2024-02-23","cited_by_count":37,"area":null},{"id":"2309.05173","title":"DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning","created":"2023-09-11","cited_by_count":35,"area":null},{"id":"2407.18369","title":"AI Safety in Generative AI Large Language Models: A Survey","created":"2024-07-06","cited_by_count":33,"area":null},{"id":"2311.11501","title":"MultiLoRA: Democratizing LoRA for Better Multi-Task Learning","created":"2023-11-20","cited_by_count":32,"area":null},{"id":"2401.12902","title":"Facing the Elephant in the Room: Visual Prompt Tuning or Full Finetuning?","created":"2024-01-23","cited_by_count":31,"area":null},{"id":"2402.15017","title":"Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning","created":"2024-02-22","cited_by_count":31,"area":null},{"id":"2408.09503","title":"Out-of-distribution generalization via composition: a lens through induction heads in Transformers","created":"2024-08-18","cited_by_count":28,"area":null},{"id":"2305.10329","title":"G-Adapter: Towards Structure-Aware Parameter-Efficient Transfer Learning for Graph Transformer Networks","created":"2023-05-17","cited_by_count":25,"area":null},{"id":"2401.00788","title":"Astraios: Parameter-Efficient Instruction Tuning Code Large Language Models","created":"2024-01-01","cited_by_count":23,"area":null},{"id":"2502.12913","title":"GSQ-Tuning: Group-Shared Exponents Integer in Fully Quantized Training for LLMs On-Device Fine-tuning","created":"2025-02-18","cited_by_count":21,"area":null},{"id":"2310.12100","title":"Non-Intrusive Adaptation: Input-Centric Parameter-efficient Fine-Tuning for Versatile Multimodal Modeling","created":"2023-10-18","cited_by_count":20,"area":"mllm"},{"id":"2505.09666","title":"System Prompt Optimization with Meta-Learning","created":"2025-05-14","cited_by_count":18,"area":null},{"id":"2307.06887","title":"Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks","created":"2023-07-13","cited_by_count":16,"area":null},{"id":"2402.10208","title":"Recovering the Pre-Fine-Tuning Weights of Generative Models","created":"2024-02-15","cited_by_count":16,"area":null},{"id":"2502.04295","title":"Beyond Prompt Content: Enhancing LLM Performance via Content-Format Integrated Prompt Optimization","created":"2025-02-06","cited_by_count":16,"area":null},{"id":"2402.04902","title":"L4Q: Parameter Efficient Quantization-Aware Fine-Tuning on Large Language Models","created":"2024-02-07","cited_by_count":15,"area":null},{"id":"2406.14979","title":"Retrieve-Plan-Generation: An Iterative Planning and Answering Framework for Knowledge-Intensive LLM Generation","created":"2024-06-21","cited_by_count":15,"area":null},{"id":"2402.02374","title":"PromptRR: Diffusion Models as Prompt Generators for Single Image Reflection Removal","created":"2024-02-04","cited_by_count":14,"area":"diffusion"},{"id":"2309.11064","title":"Exploring the Relationship between LLM Hallucinations and Prompt Linguistic Nuances: Readability, Formality, and Concreteness","created":"2023-09-20","cited_by_count":13,"area":null},{"id":"2408.01119","title":"Task Prompt Vectors: Effective Initialization through Multi-Task Soft-Prompt Transfer","created":"2024-08-02","cited_by_count":13,"area":null},{"id":"2307.08303","title":"Soft Prompt Tuning for Augmenting Dense Retrieval with Large Language Models","created":"2023-07-17","cited_by_count":12,"area":null},{"id":"2310.03331","title":"Fine-tune Language Models to Approximate Unbiased In-context Learning","created":"2023-10-05","cited_by_count":12,"area":null},{"id":"2503.10905","title":"Learning to Inference Adaptively for Multimodal Large Language Models","created":"2025-03-13","cited_by_count":12,"area":"lr"},{"id":"2401.16923","title":"Fourier Prompt Tuning for Modality-Incomplete Scene Segmentation","created":"2024-01-30","cited_by_count":11,"area":null},{"id":"2305.09025","title":"Soft Prompt Decoding for Multilingual Dense Retrieval","created":"2023-05-15","cited_by_count":10,"area":null},{"id":"2403.19113","title":"FACTOID: FACtual enTailment fOr hallucInation Detection","created":"2024-03-28","cited_by_count":10,"area":null},{"id":"2406.14036","title":"Towards Infinite-Long Prefix in Transformer","created":"2024-06-20","cited_by_count":10,"area":null},{"id":"2506.10424","title":"SOFT: Selective Data Obfuscation for Protecting LLM Fine-tuning against Membership Inference Attacks","created":"2025-06-12","cited_by_count":10,"area":"safety"},{"id":"2304.01508","title":"EPVT: Environment-aware Prompt Vision Transformer for Domain Generalization in Skin Lesion Recognition","created":"2023-04-04","cited_by_count":9,"area":null},{"id":"2404.14607","title":"Q-Tuning: Queue-based Prompt Tuning for Lifelong Few-shot Language Learning","created":"2024-04-22","cited_by_count":9,"area":null},{"id":"2505.22694","title":"MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning","created":"2025-05-28","cited_by_count":9,"area":null},{"id":"2509.18113","title":"Dynamic Prompt Fusion for Multi-Task and Cross-Domain Adaptation in LLMs","created":"2025-09-09","cited_by_count":9,"area":null},{"id":"2310.10094","title":"Decomposed Prompt Tuning via Low-Rank Reparameterization","created":"2023-10-16","cited_by_count":8,"area":null},{"id":"2401.03002","title":"Prompt-driven Latent Domain Generalization for Medical Image Classification","created":"2024-01-05","cited_by_count":8,"area":null},{"id":"2310.01691","title":"Zero-Shot Continuous Prompt Transfer: Generalizing Task Semantics Across Language Models","created":"2023-10-02","cited_by_count":7,"area":null},{"id":"2402.15082","title":"PEMT: Multi-Task Correlation Guided Mixture-of-Experts Enables Parameter-Efficient Transfer Learning","created":"2024-02-23","cited_by_count":7,"area":"moe"},{"id":"2406.19395","title":"Dataset Size Recovery from LoRA Weights","created":"2024-06-27","cited_by_count":7,"area":"safety"},{"id":"2507.06085","title":"A Survey on Prompt Tuning","created":"2025-07-08","cited_by_count":7,"area":null},{"id":"2509.23387","title":"No Loss, No Gain: Gated Refinement and Adaptive Compression for Prompt Optimization","created":"2025-09-27","cited_by_count":7,"area":null},{"id":"2310.11670","title":"Prototype-based HyperAdapter for Sample-Efficient Multi-task Tuning","created":"2023-10-18","cited_by_count":6,"area":null},{"id":"2402.11811","title":"FIPO: Free-form Instruction-oriented Prompt Optimization with Preference Dataset and Modular Fine-tuning Schema","created":"2024-02-19","cited_by_count":6,"area":null},{"id":"2403.10971","title":"Task-Aware Low-Rank Adaptation of Segment Anything Model","created":"2024-03-16","cited_by_count":6,"area":null},{"id":"2503.18063","title":"Dynamic Task Vector Grouping for Efficient Multi-Task Prompt Tuning","created":"2025-03-23","cited_by_count":6,"area":null},{"id":"2504.07357","title":"Revisiting Prompt Optimization with Large Reasoning Models-A Case Study on Event Extraction","created":"2025-04-10","cited_by_count":6,"area":"lr"},{"id":"2505.09519","title":"PT-MoE: An Efficient Finetuning Framework for Integrating Mixture-of-Experts into Prompt Tuning","created":"2025-05-14","cited_by_count":6,"area":"moe"},{"id":"2505.23473","title":"EVOREFUSE: Evolutionary Prompt Optimization for Evaluation and Mitigation of LLM Over-Refusal to Pseudo-Malicious Instructions","created":"2025-05-29","cited_by_count":6,"area":"alignment"},{"id":"2408.07081","title":"MathBridge: A Large Corpus Dataset for Translating Spoken Mathematical Expressions into $LaTeX$ Formulas for Improved Readability","created":"2024-08-07","cited_by_count":5,"area":null},{"id":"2410.08316","title":"COS-DPO: Conditioned One-Shot Multi-Objective Fine-Tuning Framework","created":"2024-10-10","cited_by_count":5,"area":"alignment"},{"id":"2509.16635","title":"Towards Anytime Retrieval: A Benchmark for Anytime Person Re-Identification","created":"2025-09-20","cited_by_count":5,"area":null},{"id":"2512.23260","title":"Interpretable Safety Alignment via SAE-Constructed Low-Rank Subspace Adaptation","created":"2025-12-29","cited_by_count":5,"area":"alignment"},{"id":"2603.03314","title":"Towards Self-Robust LLMs: Intrinsic Prompt Noise Resistance via CoIPO","created":"2026-02-09","cited_by_count":5,"area":null},{"id":"2404.05207","title":"iVPT: Improving Task-relevant Information Sharing in Visual Prompt Tuning by Cross-layer Dynamic Connection","created":"2024-04-08","cited_by_count":4,"area":null},{"id":"2410.17222","title":"Context-aware Prompt Tuning: Advancing In-Context Learning with Adversarial Methods","created":"2024-10-22","cited_by_count":4,"area":null},{"id":"2505.00009","title":"Efficient Knowledge Transfer in Multi-Task Learning through Task-Adaptive Low-Rank Representation","created":"2025-04-20","cited_by_count":4,"area":null},{"id":"2509.00421","title":"Memory Limitations of Prompt Tuning in Transformers","created":"2025-08-30","cited_by_count":4,"area":null},{"id":"2605.04970","title":"Skill Neologisms: Towards Skill-based Continual Learning","created":"2026-05-06","cited_by_count":4,"area":null},{"id":"2606.16246","title":"Demystifying Training-Time Augmentation for Data-Constrained Language Model Pretraining","created":"2026-06-15","cited_by_count":4,"area":null},{"id":"2305.13993","title":"Condensing Multilingual Knowledge with Lightweight Language-Specific Modules","created":"2023-05-23","cited_by_count":3,"area":"moe"},{"id":"2310.18358","title":"A Communication Theory Perspective on Prompting Engineering Methods for Large Language Models","created":"2023-10-24","cited_by_count":3,"area":null},{"id":"2402.08594","title":"Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning","created":"2024-02-13","cited_by_count":3,"area":null},{"id":"2402.11430","title":"EventRL: Enhancing Event Extraction with Outcome Supervision for Large Language Models","created":"2024-02-18","cited_by_count":3,"area":null},{"id":"2405.11464","title":"Efficient Prompt Tuning by Multi-Space Projection and Prompt Fusion","created":"2024-05-19","cited_by_count":3,"area":null},{"id":"2406.12251","title":"Mitigate Negative Transfer with Similarity Heuristic Lifelong Prompt Tuning","created":"2024-06-18","cited_by_count":3,"area":null},{"id":"2411.17426","title":"CLOVER: Cross-Layer Orthogonal Vectors Pruning and Fine-Tuning","created":"2024-11-26","cited_by_count":3,"area":null},{"id":"2501.03291","title":"ADePT: Adaptive Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning","created":"2025-01-06","cited_by_count":3,"area":null},{"id":"2502.12200","title":"Efficient and Effective Prompt Tuning via Prompt Decomposition and Compressed Outer Product","created":"2025-02-16","cited_by_count":3,"area":null},{"id":"2505.00582","title":"Block Circulant Adapter for Large Language Models","created":"2025-05-01","cited_by_count":3,"area":null},{"id":"2310.01217","title":"ScaLearn: Simple and Highly Parameter-Efficient Task Transfer by Learning to Scale","created":"2023-10-02","cited_by_count":2,"area":null},{"id":"2403.18976","title":"\"Sorry, Come Again?\" Prompting -- Enhancing Comprehension and Diminishing Hallucination with [PAUSE]-injected Optimal Paraphrasing","created":"2024-03-27","cited_by_count":2,"area":null},{"id":"2405.20654","title":"Passage-specific Prompt Tuning for Passage Reranking in Question Answering with Large Language Models","created":"2024-05-31","cited_by_count":2,"area":null},{"id":"2406.05279","title":"SuperPos-Prompt: Enhancing Soft Prompt Tuning of Language Models with Superposition of Multi Token Embeddings","created":"2024-06-07","cited_by_count":2,"area":null},{"id":"2406.19486","title":"LoPT: Low-Rank Prompt Tuning for Parameter Efficient Language Models","created":"2024-06-27","cited_by_count":2,"area":null},{"id":"2408.13227","title":"Enhancing Few-Shot Transfer Learning with Optimized Multi-Task Prompt Tuning through Modular Prompt Composition","created":"2024-08-23","cited_by_count":2,"area":null},{"id":"2504.09069","title":"UniFlowRestore: A General Video Restoration Framework via Flow Matching and Prompt Guidance","created":"2025-04-12","cited_by_count":2,"area":"diffusion"},{"id":"2507.09839","title":"Stabilizing Black-Box Prompt Optimization with Textual Regularization and Signal Aggregation","created":"2025-07-14","cited_by_count":2,"area":null},{"id":"2603.12645","title":"LightMoE: Reducing Mixture-of-Experts Redundancy through Expert Replacing","created":"2026-03-13","cited_by_count":2,"area":"moe"},{"id":"2403.06745","title":"ACT-MNMT Auto-Constriction Turning for Multilingual Neural Machine Translation","created":"2024-03-11","cited_by_count":1,"area":null},{"id":"2410.12847","title":"ACCEPT: Adaptive Codebook for Composite and Efficient Prompt Tuning","created":"2024-10-10","cited_by_count":1,"area":null},{"id":"2505.23386","title":"VModA: An Effective Framework for Adaptive NSFW Image Moderation","created":"2025-05-29","cited_by_count":1,"area":null},{"id":"2507.14725","title":"GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning","created":"2025-07-19","cited_by_count":1,"area":null},{"id":"2609.15972","title":"Mind2Dialogue: Training Human-Aware Language Models by Simulating User Mental States","created":"2026-09-14","cited_by_count":1,"area":null},{"id":"2310.02473","title":"Prompting-based Temporal Domain Generalization","created":"2023-10-03","cited_by_count":0,"area":null},{"id":"2402.17934","title":"Inducing Generalization across Languages and Tasks using Featurized Low-Rank Mixtures","created":"2024-02-27","cited_by_count":0,"area":null},{"id":"2504.12311","title":"Learning Optimal Prompt Ensemble for Multi-source Visual Prompt Transfer","created":"2025-04-09","cited_by_count":0,"area":null},{"id":"2505.20933","title":"Information-Theoretic Complementary Prompts for Improved Continual Text Classification","created":"2025-05-27","cited_by_count":0,"area":null}],"next_cursor":"100"}