8 citations · 8 across the 2 of their papers we have counts for
9 papers · 1 filter
Not-Just-Scaling Laws: Towards a Better Understanding of the Downstream Impact of Language Model Design Decisions
Emmy Liu, Amanda Bertsch, Lintang Sutawika +9
Improvements in language model capabilities are often attributed to increasing model size or training data, but in some cases smaller models trained on curated data or with differe…
MEDDxAgent: A Unified Modular Agent Framework for Explainable Automatic Differential Diagnosis
Daniel Rose, Chia-Chien Hung, Marco Lepri +3
Differential Diagnosis (DDx) is a fundamental yet complex aspect of clinical decision-making, in which physicians iteratively refine a ranked list of possible diseases based on sym…
Evaluating Language Models as Synthetic Data Generators
Seungone Kim, Juyoung Suk, Xiang Yue +7
Given the increasing use of synthetic data in language model (LM) post-training, an LM's ability to generate high-quality data has become nearly as crucial as its ability to solve…
LightPAL: Lightweight Passage Retrieval for Open Domain Multi-Document Summarization
Masafumi Enomoto, Kunihiro Takeoka, Kosuke Akimoto +2
Open-Domain Multi-Document Summarization (ODMDS) is the task of generating summaries from large document collections in response to user queries. This task is crucial for efficient…
Robust Text Classification: Analyzing Prototype-Based Networks
Zhivar Sourati, Darshan Deshpande, Filip Ilievski +2
Downstream applications often require text classification models to be accurate and robust. While the accuracy of the state-of-the-art Language Models (LMs) approximates human perf…
Linking Surface Facts to Large-Scale Knowledge Graphs
Gorjan Radevski, Kiril Gashteovski, Chia-Chien Hung +2
Open Information Extraction (OIE) methods extract facts from natural language text in the form of ("subject"; "relation"; "object") triples. These facts are, however, merely surfac…