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COLM 2024 : Conference on Language Modeling

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Link: https://colmweb.org/
 
When Oct 7, 2024 - Oct 9, 2024
Where Philadelphia, PA
Abstract Registration Due Mar 22, 2024
Submission Deadline Mar 29, 2024
Notification Due Jul 9, 2024
Categories    machine learning   artificial intelligence   nature language processing   language models
 

Call For Papers

We consider a broad range of subject areas focused on language modeling for the first iteration of COLM. We consider the term "language model" in the broadest way. A non-exhaustive list of topics of interests includes:

* All about alignment: fine-tuning, instruction-tuning, reinforcement learning (with human feedback), prompt tuning, and in-context alignment

* All about data: pre-training data, alignment data, and synthetic data --- via manual or algorithmic analysis, curation, and generation

* All about evaluation: benchmarks, simulation environments, scalable oversight, evaluation protocols and metrics, human and/or machine evaluation

* All about societal implications: bias, equity, misuse, jobs, climate change, and beyond

* All about safety: security, privacy, misinformation, adversarial attacks and defenses

* Science of LMs: scaling laws, fundamental limitations, emergent capabilities, demystification, interpretability, complexity, training dynamics, grokking, learning theory for LMs

* Compute efficient LMs: distillation, compression, quantization, sample efficient methods, memory efficient methods

* Engineering for large LMs: distributed training and inference on different hardware setups, training dynamics, optimization instability

* Learning algorithms for LMs: learning, unlearning, meta learning, model mixing methods, continual learning

* Inference algorithms for LMs: decoding algorithms, reasoning algorithms, search algorithms, planning algorithms

* Human mind, brain, philosophy, laws and LMs: cognitive science, neuroscience, linguistics, psycholinguistics, philosophical, or legal perspectives on LMs

* LMs for everyone: multi-linguality, low-resource languages, vernacular languages, multiculturalism, value pluralism

* LMs and the world: factuality, retrieval-augmented LMs, knowledge models, commonsense reasoning, theory of mind, social norms, pragmatics, and world models

* LMs and embodiment: perception, action, robotics, and multimodality

* LMs and interactions: conversation, interactive learning, and multi-agents learning

* LMs with tools and code: integration with tools and APIs, LM-driven software engineering

* LMs on diverse modalities and novel applications: visual LMs, code LMs, math LMs, and so forth, with extra encouragements for less studied modalities or applications such as chemistry, medicine, education, database and beyond

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