36 citations · 62 across the 21 of their papers we have counts for
11 papers · 1 filter
SkillFactory: Self-Distillation For Learning Cognitive Behaviors
Zayne Sprague, Jack Lu, Manya Wadhwa +3
Reasoning models leveraging long chains of thought employ various cognitive skills, such as verification of their answers, backtracking, retrying by an alternate method, and more.…
SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages
Holy Lovenia, Rahmad Mahendra, Salsabil Maulana Akbar +58
Southeast Asia (SEA) is a region rich in linguistic diversity and cultural variety, with over 1,300 indigenous languages and a population of 671 million people. However, prevailing…
Linearizing Large Language Models
Jean Mercat, Igor Vasiljevic, Sedrick Keh +4
Linear transformers have emerged as a subquadratic-time alternative to softmax attention and have garnered significant interest due to their fixed-size recurrent state that lowers…
Language models scale reliably with over-training and on downstream tasks
Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar +22
Scaling laws are useful guides for derisking expensive training runs, as they predict performance of large models using cheaper, small-scale experiments. However, there remain gaps…
Where It Really Matters: Few-Shot Environmental Conservation Media Monitoring for Low-Resource Languages
Sameer Jain, Sedrick Scott Keh, Shova Chettri +8
Environmental conservation organizations routinely monitor news content on conservation in protected areas to maintain situational awareness of developments that can have an enviro…
Asking More Informative Questions for Grounded Retrieval
Sedrick Keh, Justin T. Chiu, Daniel Fried
When a model is trying to gather information in an interactive setting, it benefits from asking informative questions. However, in the case of a grounded multi-turn image identific…
Hashtag-Guided Low-Resource Tweet Classification
Shizhe Diao, Sedrick Scott Keh, Liangming Pan +3
Social media classification tasks (e.g., tweet sentiment analysis, tweet stance detection) are challenging because social media posts are typically short, informal, and ambiguous.…
Exploring Euphemism Detection in Few-Shot and Zero-Shot Settings
Sedrick Scott Keh
This work builds upon the Euphemism Detection Shared Task proposed in the EMNLP 2022 FigLang Workshop, and extends it to few-shot and zero-shot settings. We demonstrate a few-shot…
EUREKA: EUphemism Recognition Enhanced through Knn-based methods and Augmentation
Sedrick Scott Keh, Rohit K. Bharadwaj, Emmy Liu +3
We introduce EUREKA, an ensemble-based approach for performing automatic euphemism detection. We (1) identify and correct potentially mislabelled rows in the dataset, (2) curate an…
PINEAPPLE: Personifying INanimate Entities by Acquiring Parallel Personification data for Learning Enhanced generation
Sedrick Scott Keh, Kevin Lu, Varun Gangal +4
A personification is a figure of speech that endows inanimate entities with properties and actions typically seen as requiring animacy. In this paper, we explore the task of person…
PANCETTA: Phoneme Aware Neural Completion to Elicit Tongue Twisters Automatically
Sedrick Scott Keh, Steven Y. Feng, Varun Gangal +2
Tongue twisters are meaningful sentences that are difficult to pronounce. The process of automatically generating tongue twisters is challenging since the generated utterance must…