NeurIPS 2024PastLarge language modelsEfficiency
Adaptive Foundation Models: Evolving AI for Personalized and Efficient Learning
AFM 2024
- Submission deadline
- Oct 5, 2024, 12:00 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (128)
Fetched from OpenReview (v2) on 2026-06-10.
$\text{Transformer}^2$: Self-adaptive LLMs
A Common Pitfall of Margin-based Language Model Alignment: Gradient Entanglement
Accelerated Preference Optimization for Large Language Model Alignment
AdaptAgent: Adapting Multimodal Web Agents with Few-Shot Learning from Human Demonstrations
Adapting Foundation Models via Training-free Dynamic Weight Interpolation
Adapting Language Models via Token Translation
Adaptive LoRA Merging for Efficient Domain Incremental Learning
Adaptive World Models: Learning Behaviors by Latent Imagination Under Non-Stationarity
Agent Skill Acquisition for LLMs via CycleQD
AgentMerge: Enhancing Generalization in Fine-Tuned LLM Agents
AoP-SAM: Automation of Prompts for Efficient Segmentation
APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding
Approximate Top-k for Increased Parallelism
Are LLMs Prescient? A Continuous Evaluation using Daily News as the Oracle
Assisted Few-Shot Learning for Vision-Language Models in Agricultural Stress Phenotype Identification
Automated Design of Agentic Systems
Automatically Generating Custom Context-Driven SFT Data for LLMs with Multi-Granularity
Better Prompt Compression Without Multi-Layer Perceptrons
Can the Spectrum of the Neural Tangent Kernel Anticipate Fine-Tuning Performance?
Can Vision Language Models Learn from Visual Demonstrations of Ambiguous Spatial Reasoning?
CAT Pruning: Cluster-Aware Token Pruning For Text-to-Image Diffusion Models
CITER: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level Routing
Combining Domain and Alignment Vectors to Achieve Better Knowledge-Safety Trade-offs in LLMs
Continuous Language Model Interpolation for Dynamic and Controllable Text Generation
Controlling Forgetting with Test-Time Data in Continual Learning
Controlling Multimodal LLMs via Reward-guided Decoding
COrAL: Order-Agnostic Language Modeling for Efficient Iterative Refinement
CTRL-O: Language-Controllable Object-Centric Visual Representation Learning
Data-Efficient Training by Evolved Sampling
Deliberate Practice with Synthetic Data
Device-Directed Speech Detection for Follow-up Conversations Using Large Language Models
Do Think Tags Really Help LLMs Plan? A Critical Evaluation of ReAct-Style Prompting
Domain Adaptation for Robust Model Routing
DuoDiff: Accelerating Diffusion Models with a Dual-Backbone Approach
Dynamic Subset Tuning: Expanding the Operational Range of Parameter-Efficient Training for Large Language Models
Dynamically Managing a Prompt Pool via Self-Enhancement in Continual Learning
Effective Text-to-Image Alignment with Quality Aware Pair Ranking
Efficient Domain Adaptation of Robotic Foundation Models via Hypernetwork-Generated LoRA
Efficient Fine-Tuning of Image-Conditional Diffusion Models for Depth and Surface Normal Estimation
Efficient Transfer Learning driven by Layer-wise Features Aggregation
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs
Embodied-RAG: General Non-parametric Embodied Memory for Retrieval and Generation
Empowering LLM Agents with Zero-Shot Optimal Decision-Making through Q-learning
Enhancing Cross-Language Code Translation via Task-Specific Embedding Alignment in Retrieval-Augmented Generation
Enhancing Fine-Tuning Efficiency of LLMs Through Gradient Subspace Tracking
Enhancing Long Context Performance in LLMs Through Inner Loop Query Mechanism
Enhancing Multi-Agent Multi-Modal Collaboration with Fine-Grained Reward Modeling
Enhancing Reasoning to Adapt Large Language Models for Domain-Specific Applications
Ensemble-based Offline Reinforcement Learning with Adaptive Behavior Cloning
Evaluating RAG System Performance: The Impact of Knowledge Cut-off and Fine-Tuning
Exploring Visual Prompt Tuning for Demographic Adaptation in Foundation Models for Medical Imaging
Extracting Parallelism from Large Language Model Queries
Fast and Accurate Language Model Decoding via Parallel Token Processing
Fine-Grained Visual Recognition in the Age of Multimodal LLMs
Fine-tuning LLM Agents with Retrospective In-Context Online Learning
FlashDP: Memory-Efficient and High-Throughput DP-SGD Training for Large Language Models
From One to Zero: RAG-IM Adapts Language Models for Interpretable Zero-Shot Clinical Predictions
Fully-inductive Node Classification on Arbitrary Graphs
Generating Diverse Negations from Affirmative Sentences
Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass
GraphText: Graph Reasoning in Text Space
IFCap: Image-like Retrieval and Frequency-based Entity Filtering for Zero-shot Captioning
Imbalance-Regularized LoRA: A Plug-and-Play Method for Improving Fine-Tuning of Foundation Models
Improving In-Context Learning with Small Language Model Ensembles
Improving Model Merging with Natural Niches
In-Context Learning behaves as a greedy layer-wise gradient descent algorithm
Informed Tree of Thought: Cost-efficient Problem Solving with Large Language Models
Instant Transformer Adaption via HyperLoRA
InstructRAG: Instructing Retrieval Augmented Generation via Self-Synthesized Rationales
InvestAlign: Align LLMs with Investor Decision-Making under Herd Behavior
Is In-Context Learning Sufficient for Instruction Following in LLMs?
LangDA: Language-guided Domain Adaptive Semantic Segmentation
Leveraging Self Weak-supervision for Improved VLM Performance
LinkGPT: Teaching Large Language Models To Predict Missing Links
Long Context RAG Performance of Large Language Models
LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory
MagicPIG: LSH Sampling for Efficient LLM Generation
MD-DiT: Step-aware Mixture-of-Depths for Efficient Diffusion Transformers
Memory Efficient Continual Learning with CLIP Models
MESS+: Energy-Optimal Inferencing in Language Model Zoos with Service Level Guarantees
metaTextGrad: Learning to learn with language models as optimizers
Mitigating Hallucination in Large Vision-Language Models via Modular Attribution and Intervention
MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models
MMIE: Massive Multimodal Interleaved Comprehension Benchmark for Large Vision-Language Models
Model Developmental Safety: A Safety-Centric Method and Applications in Vision-Language Models
N-Gram Induction Heads for In-Context RL: Improving Stability and Reducing Data Needs
Narrow Transformer: Mono-lingual Code SLM for Desktop
NegMerge: Consensual Weight Negation for Strong Machine Unlearning
Nexus: Specialization meets Adaptability for Efficiently Training Mixture of Experts
OmniPredict: GPT-4o Enhanced Multi-modal Pedestrian Crossing Intention Prediction
On Pre-training of Multimodal Language Models Customized for Chart Understanding
One Initialization to Rule them All: Fine-tuning via Explained Variance Adaptation
P3O: Pessimistic Preference-based Policy Optimization for Robust Alignment from Preferences
PAL: Pluralistic Alignment Framework for Learning from Heterogeneous Preferences
Personalized Adaptation via In-Context Preference Learning
Personalized Language Modeling from Personalized Human Feedback
Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging
Personas within Parameters: Fine-Tuning Small Language Models with Low-Rank Adapters to Mimic User Behaviors
Pick Your Influencer: Being Selective is Good for Personalization
PM-Jewelry: Personalized Multimodal Adaptation for Virtual Jewelry Try-On with Latent Diffusion
Pre-trained Language Models Improve the Few-shot Prompt Ability of Decision Transformer
Prompt Learning Based Adaptor for Enhanced Video Editing with Pretrained Text-to-Image Diffusion Models
RAGGED: Towards Informed Design of Retrieval Augmented Generation Systems
REGENT: A Retrieval-Augmented Generalist Agent That Can Act in-Context In New Environments
Retrieval-Augmented Data Augmentation for Low-Resource Domain Tasks
SeCom: On Memory Construction and Retrieval for Personalized Conversational Agents
Self-Play Preference Optimization for Language Model Alignment
Sirius: Contextual Sparsity with Correction for Efficient LLM
Situated Instruction Following Under Ambiguous Human Intent
Slaying the HyDRA: Parameter-Efficient Hyper Networks with Low-Displacement Rank Adaptation
SpikingVTG: Saliency Feedback Gating Enabled Spiking Video Temporal Grounding
Synergistic Weak-Strong Collaboration by Aligning Preferences
Tensor Attention Training: Provably Efficient Learning of Higher-order Transformers
Text as Images: Can Multimodal Large Language Models Follow Printed Instructions in Pixels?
Towards Conversational AI for Spina Bifida Care
Towards Federated Low-Rank Adaptation with Rank Heterogeneity
Towards Full Delegation: Designing Ideal Agentic Behaviors for Travel Planning
Towards Personalized Language Models via Inference-time Human Preference Optimization
Towards Robust and Cost-Efficient Knowledge Unlearning for Large Language Models
Transfer Learning for Finetuning Large Language Models
Uncertainty-Penalized Direct Preference Optimization
Understanding Visual Concepts Across Models
Uniform Text-Motion Generation and Editing via Diffusion Model
ViPCap: Retrieval Text-based Visual Prompts for Lightweight Image Captioning
Visual Language Alignment Tuning
Warmstarting for Scaling Language Models
XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning
ZO-Offloading: Fine-Tuning LLMs with 100 Billion Parameters on a Single GPU