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Augmented LMs, understanding and mitigating failure modes of LMs

Language for robots, LLM-based planning, other signals

Hardware algorithms, long context generation, FMs for new material

System support for ML, LLMs on local devices, scaling open language models

Multiagent systems, ethics, societal implication

Sparse training and inference, low-bit quantization of LLMs, agent systems, agents for science

Trustworthy NLP, responsible AI, controllable natural language generation, computational social science

Foundation models for music

Robot learning, mobile manipulation, sensing, human-robot interaction

LLMs in safety/privacy risk situations, code verification, neuro-symbolic methods

Pragmatics of language, context, generating/following instructions, code models, interfaces, multimodal dialog

Finetuning LLMs for neuro-symbolic reasoning, autonomous scientific research, robotics

State space models, network architectures, audio models

Robotics, machine learning, computer vision

Generative language models for coherent and engaging narratives, leveraging models as creative tools

Chemistry, machine learning, molecular modeling, quantum mechanics

Support for LLMs, computational efficiency, speculative execution, GPU memory

LLMs, efficient fine-tuning, inference

Reinforcement learning (RL), foundation models and reinforcement learning

Large Language Models, Multilingual NLP, AI for Science

NLP in medicine, decision support, evaluation outside labeled datasets, robustness

LLMs for molecular and cell biology, Single-cell genomics, AI for biomedicine

Distributed and concurrent computation, programming languages

Interactive and Visual Data Science, Interpretable Machine Learning, Data-Driven Healthcare

Algorithms for finetuning foundation models, robustness/reliability, understanding representation

Vision language models, long-tailed recognition, image generation

Multimodal models, visual language reasoning

Ethical risks, LLM limitations w.r.t. reasoning, social intelligence

Active learning, data mining, reinforcement learning, optimization, intelligent control

Autonomous decision making, human-AI complementarity, reinforcement learning, LLM alignment

Privacy, robustness, finetuning, LLM validation, federated learning

Efficiency of LLMs, computation, data, applications outside CS

Multimodal learning, Human-AI Collaboration, LLM Evaluation

Cognitive Science, Computational Cognitive Neuroscience, NeuroAI, Perception, Vision

Foundation models for speech

LLMs for math and theorem proving, inference algorithms

Intersection of HCI and NLP, model mapping to use cases

Responsible AI, Interactive learning, Economic aspects of machine learning

System support for LLMs, pretraining, finetuning, federated learning, private inference, acceleration, Vicuna model, AI for science

Computer vision, graphics, computational photography, generative models