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Found 17 papers, 8 papers with code
2 OLMo 2 Furious
Our modified model architecture and training recipe achieve both better training stability and improved per-token efficiency.
Tulu 3: Pushing Frontiers in Open Language Model Post-Training
Language model post-training is applied to refine behaviors and unlock new skills across a wide range of recent language models, but open recipes for applying these techniques lag behind proprietary ones.
SimpleToM: Exposing the Gap between Explicit ToM Inference and Implicit ToM Application in LLMs
"), and (c) judgment ("Mary paid for the chips.
OLMoE: Open Mixture-of-Experts Language Models
We introduce OLMoE, a fully open, state-of-the-art language model leveraging sparse Mixture-of-Experts (MoE).
OLMES: A Standard for Language Model Evaluations
Evaluating language models in particular is challenging, as small changes to how a model is evaluated on a task can lead to large changes in measured performance.
WorldValuesBench: A Large-Scale Benchmark Dataset for Multi-Cultural Value Awareness of Language Models
The awareness of multi-cultural human values is critical to the ability of language models (LMs) to generate safe and personalized responses.
PROC2PDDL: Open-Domain Planning Representations from Texts
Planning in a text-based environment continues to be a major challenge for AI systems.
OLMo: Accelerating the Science of Language Models
Given the importance of these details in scientifically studying these models, including their biases and potential risks, we believe it is essential for the research community to have access to powerful, truly open LMs.
Digital Socrates: Evaluating LLMs through Explanation Critiques
While LLMs can provide reasoned explanations along with their answers, the nature and quality of those explanations are still poorly understood.
What Makes it Ok to Set a Fire? Iterative Self-distillation of Contexts and Rationales for Disambiguating Defeasible Social and Moral Situations
From this model we distill a high-quality dataset, \delta-Rules-of-Thumb, of 1. 2M entries of contextualizations and rationales for 115K defeasible moral actions rated highly by human annotators 85. 9% to 99. 8% of the time.
Do language models have coherent mental models of everyday things?
Using these questions as probes, we observe that state-of-the-art pre-trained language models (LMs) like GPT-3 and Macaw have fragments of knowledge about these everyday things, but do not have fully coherent "parts mental models" (54-59% accurate, 19-43% conditional constraint violation).
Measure More, Question More: Experimental Studies on Transformer-based Language Models and Complement Coercion
Transformer-based language models have shown strong performance on an array of natural language understanding tasks.
One Venue, Two Conferences: The Separation of Chinese and American Citation Networks
At NeurIPS, American and Chinese institutions cite papers from each other's regions substantially less than they cite endogamously.
Just-DREAM-about-it: Figurative Language Understanding with DREAM-FLUTE
We hypothesize that to perform this task well, the reader needs to mentally elaborate the scene being described to identify a sensible meaning of the language.
Large-Scale Acoustic Characterization of Singaporean Children's English Pronunciation
In tense and lax vowel pairs, we also consistently observe that the distinction is less conspicuous for Singaporean children compared to the other speaker groups.
DREAM: Improving Situational QA by First Elaborating the Situation
To test this conjecture, we train a new model, DREAM, to answer questions that elaborate the scenes that situated questions are about, and then provide those elaborations as additional context to a question-answering (QA) model.
Acoustic Characterization of Singaporean Children's English: Comparisons to American and British Counterparts
We investigate English pronunciation patterns in Singaporean children in relation to their American and British counterparts by conducting archetypal analysis on selected vowel pairs.
