ICML 2024PastLarge language models
ICML 2024 Workshop on Foundation Models in the Wild
ICML 2024 FM-Wild Workshop
- Submission deadline
- Jun 8, 2024, 12:29 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (95)
Fetched from OpenReview (v2) on 2026-06-10.
$\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs
A Critical Look At Tokenwise Reward-Guided Text Generation
Adapting LLM Agents with Universal Feedback in Communication
Adaptive Concept Bottleneck for Foundation Models
AdaptiveBackdoor: Backdoored Language Model Agents that Detect Human Overseers
Adversarially Robust CLIP Models Induce Better (Robust) Perceptual Metrics
An Auditing Test to Detect Behavioral Shift in Language Models
An Empirical Study into Clustering of Unseen Datasets with Self-Supervised Foundation Models
Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasks
Bilingual Adaptation of Monolingual Foundation Models
Black-Box Detection of Language Model Watermarks
BUILD: Buffer-free Incremental Learning with OOD Detection for the Wild
Calibrated Self-Rewarding Vision Language Models
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
CharED: Character-wise Ensemble Decoding for Large Language Models
Code Agents are State of The Art Software Testers
Combining Pre-trained LoRA Modules Improves Few-shot Adaptation of Foundation Models to New Tasks
ContextCite: Attributing Model Generation to Context
Data Mixture Inference: What do BPE Tokenizers Reveal about their Training Data?
DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning
DistilDIRE: A Small, Fast, Cheap and Lightweight Diffusion Synthesized Deepfake Detection
Domain-Aware Fine-Tuning of Foundation Models
Dual Risk Minimization for Robust Fine-tuning of Zero-Shot Models
Efficient Evolutionary Search over Chemical Space with Large Language Models
End-To-End Causal Effect Estimation from Unstructured Natural Language Data
Estimating Probability Densities of Tabular Data using a Transformer Model combined with Denoising Diffusion
Evaluating Self-Supervised Foundation Models in Holographic Imaging
Evaluation of RAG Metrics for Question Answering in the Telecom Domain
ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts
Extracting Training Data from Document-Based VQA Models
Extrapolative Protein Design through Triplet-based Preference Learning
Federated Fine-Tuning of Vision Foundation Models via Probabilistic Masking
Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models
FoMu-SSL: Foundation Model-Guided Multi-Sensor Self-Supervised Learning for Remote Sensing
Generalization vs. Memorization: Tracing Language Models' Capabilities Back to Pretraining Data
Geometric Median Matching for Robust Data Pruning
GROD: Enhancing Generalization of Transformer with Out-of-Distribution Detection
Improving GFlowNets for Text-to-Image Diffusion Alignment
Improving Graph-Language Alignment with Hierarchical Graph Tokenization
In Search of Forgotten Domain Generalization
In-Context Learning Improves Compositional Understanding of Vision-Language Models
Inference Performance Optimization for Large Language Models on CPUs
InstructBooth: Instruction-following Personalized Text-to-Image Generation
Instruction Tuning With Loss Over Instructions
Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data
It Takes Two: On the Seamlessness between Reward and Policy Model in RLHF
Jogging the Memory of Unlearned Models Through Targeted Relearning Attacks
Language Model-In-The-Loop: Data Optimal Approach to Recommend Actions in Text Games
Leveraging Generative Foundation Models for Domain Generalization
LIFTED: Multimodal Mixture-of-Experts for Clinical Trial Outcome Prediction
LLM Task Interference: Impact of Task-Switch in Conversational History
LoRD: Low-Rank Decomposition of Monolingual Code LLMs for One-Shot Compression
Merging Improves Self-Critique Against Jailbreak Attacks
MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge?
Model Breadcrumbs: Scalable Upcycling of Finetuned Foundation Models via Sparse Task Vectors Merging
MoRe Fine-Tuning with 10x Fewer Parameters
Not Just Pretty Pictures: Toward Interventional Data Augmentation Using Text-to-Image Generators
On the Discrepancy and Connection between Memorization and Generation in Diffusion Models
On the Privacy Risks of Post-Hoc Explanations of Foundation Models
Open LLMs are Necessary for Private Adaptations and Outperform their Closed Alternatives
OTTER: Effortless Label Distribution Adaptation of Zero-shot Models
Out-Of-Context Prompting Boosts Fairness and Robustness in Large Language Model Predictions
PanSAM: Zero-Shot, Prompt-Free Pancreas Segmentation in CT Imaging
Parameter-Efficient Quantized Mixture-of-Experts Meets Vision-Language Instruction Tuning for Semiconductor Electron Micrograph Analysis
PLUTO: Pathology-Universal Transformer
POST: A Framework for Privacy of Soft-prompt Transfer
Pretrained Hybrids with MAD Skills
Privacy Auditing of Large Language Models
Private Fine-tuning of Large Language Models with Zeroth-order Optimization
Projected Language Models: A Large Model Pre-Segmented Into Smaller Ones
Quantum 3D Visual Grounding: A Step Towards Quantum-inspired AI-Visualization
Rapid Switching and Multi-Adapter Fusion via Sparse High Rank Adapters
Recursive Introspection: Teaching LLM Agents How to Self-Improve
RNR: Teaching Large Language Models to Follow Roles and Rules
RouteFinder: Towards Foundation Models for Vehicle Routing Problems
SEE-2-SOUND: Zero-Shot Spatial Environment-to-Spatial Sound
Self-Control of LLM Behaviors by Compressing Suffix Gradient into Prefix Controller
Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs
Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs
Strong Copyright Protection for Language Models via Adaptive Model Fusion
Test-Time Prototype Evolution for Generalizable Vision-Language Models
The Effect of Data Corruption on Multimodal Long Form Responses
TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model
Towards Safe Large Language Models for Medicine
TriLM vs FloatLM: Ternary LLMs are more Performant than Quantized FP16 LLMs
Two-Level Test-Time Adaptation in Multimodal Learning
Understanding the Role of Functional Diversity in Weight-Ensembling with Ingredient Selection and Multidimensional Scaling
Unsupervised Feature Extraction from a Foundation Model Zoo for Cell Similarity Search in Oncological Microscopy Across Devices
Unveiling CLIP Dynamics: Linear Mode Connectivity and Generalization
USCILab3D: A Large-scale, Long-term, Semantically Annotated Outdoor Dataset
VFA: Vision Frequency Analysis of Foundation Models and Human
Vision-Language Models Provide Promptable Representations for Reinforcement Learning
Waterfall: Framework for Robust and Scalable Text Watermarking
When Do Language Models Need to Be Large?
Zero-Shot Generalization of GNNs over Distinct Attribute Domains