Overview
The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.
Sponsorship Details
Platinum
Booth #J08
Workshops
ICLR 2025 Workshop on Sparsity in LLMs
April 27
ICLR 2025 Workshop on Foundation Models in the Wild
April 27
In the era of AI-driven transformations, foundation models (FMs) have become pivotal in various applications, from natural language processing to computer vision. These models, with their immense capabilities, reshape the future of scientific research and the broader human society, but also introduce challenges in their in-the-wild deployments. The Workshop on FMs in the wild delves into the urgent need for these models to be useful when deployed in our societies. The significance of this topic cannot be overstated, as the real-world implications of these models impact everything from daily information access to critical decision-making in fields like medicine and finance. Stakeholders, from developers to end-users, care deeply about this because the successful integration of FMs into in-the-wild frameworks necessitates a careful consideration of many properties, including adaptivity, reliability, efficiency, and reasoning ability.
Website: https://fm-wild-community.github.io/
Website: https://fm-wild-community.github.io/
Meet a scientist
Thursday, April 24
April 24
10:00am - 10:30am
Research domains
- Agents
- Agents for coding
- Bandits
- Computer vision
- Continual learning
- Generative AI
- Large language models (LLMs)
- Machine learning
- Multimodal retrieval
12:30pm - 1:00pm
Research domains
- Agents
- AutoML
- Causal inference
- Generative AI
- Graph neural networks (GNNs)
- GraphML
- LLMs
- Natural language processing (NLP)
- Reinforcement Learning
- Retrieval
3:00pm - 3:30pm
Research domains
- Agents
- Efficient ML
- Generative AI
- GNNs
- Graph ML
- LLMs
- MLSys
- NLP
- Reinforcement learning
- Retrieval
Research domains
- Agents
- Agents for coding
- Bandits
- Computer vision
- Continual learning
- Generative AI
- Large language models (LLMs)
- Machine learning
- Multimodal retrieval
12:30pm - 1:00pm
Research domains
- Agents
- AutoML
- Causal inference
- Generative AI
- Graph neural networks (GNNs)
- GraphML
- LLMs
- Natural language processing (NLP)
- Reinforcement Learning
- Retrieval
3:00pm - 3:30pm
Research domains
- Agents
- Efficient ML
- Generative AI
- GNNs
- Graph ML
- LLMs
- MLSys
- NLP
- Reinforcement learning
- Retrieval
Friday, April 25
April 25
10:00am - 10:30am
Research domains
- Agents
- Generative AI
- GraphML
- Large language models (LLMs)
- Losses
- Machine learning
- Multimodal
- Natural language processing (NLP)
- Time series forecasting
12:30pm - 1:00pm
Research domains
- Agents for coding
- Bandits
- Continual learning
- Generative AI
- LLMs
- MLSys
- Multimodal
- Reinforcement learning
- Retrieval
3:00pm - 3:30pm
Research domains
- Agents
- AI for science
- Causal inference
- Computer vision
- Generative AI
- Graph neural networks
- Graph ML
- LLMs
- Machine learning
- Reinforcement learning
- Retrieval
Research domains
- Agents
- Generative AI
- GraphML
- Large language models (LLMs)
- Losses
- Machine learning
- Multimodal
- Natural language processing (NLP)
- Time series forecasting
12:30pm - 1:00pm
Research domains
- Agents for coding
- Bandits
- Continual learning
- Generative AI
- LLMs
- MLSys
- Multimodal
- Reinforcement learning
- Retrieval
3:00pm - 3:30pm
Research domains
- Agents
- AI for science
- Causal inference
- Computer vision
- Generative AI
- Graph neural networks
- Graph ML
- LLMs
- Machine learning
- Reinforcement learning
- Retrieval
Saturday, April 26
April 26
10:00am - 10:30am
Research domains
- Agents
- Auto ML
- Generative AI
- Graph ML
- Large language models (LLMs)
- Natural language processing (NLP)
- Reinforcement learning
- Retrieval
12:30pm - 1:00pm
Research domains
- Agents
- Efficient ML
- Generative AI
- Graph neural networks
- Graph ML
- LLMs
- Machine learning
- NLP
- Time series forecasting
3:00pm - 3:30pm
Research domains
- Agents
- AI for science
- Generative AI
- LLMs
- Losses
- Machine learning
- Multimodal
- NLP
- Reinforcement learning
Research domains
- Agents
- Auto ML
- Generative AI
- Graph ML
- Large language models (LLMs)
- Natural language processing (NLP)
- Reinforcement learning
- Retrieval
12:30pm - 1:00pm
Research domains
- Agents
- Efficient ML
- Generative AI
- Graph neural networks
- Graph ML
- LLMs
- Machine learning
- NLP
- Time series forecasting
3:00pm - 3:30pm
Research domains
- Agents
- AI for science
- Generative AI
- LLMs
- Losses
- Machine learning
- Multimodal
- NLP
- Reinforcement learning
Latest news
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April 11, 2025Novel three-pronged approach combines claim-level evaluations, chain-of-thought reasoning, and classification of hallucination error types.
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April 10, 2025New tool lets customers build, train, and deploy machine learning models using only natural language.
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March 27, 2025Training separate models on different datasets and then merging them reduces computational costs by as much as 91%.