68 citations · 114 across the 25 of their papers we have counts for
9 papers · 1 filter
SkipSNN: Efficiently Classifying Spike Trains with Event-attention
Hang Yin, Yao Su, Liping Liu +3
Spike train classification has recently become an important topic in the machine learning community, where each spike train is a binary event sequence with \emph{temporal-sparsity…
BraVE: Offline Reinforcement Learning for Discrete Combinatorial Action Spaces
Matthew Landers, Taylor W. Killian, Hugo Barnes +2
Offline reinforcement learning in high-dimensional, discrete action spaces is challenging due to the exponential scaling of the joint action space with the number of sub-actions an…
Composable Interventions for Language Models
Arinbjorn Kolbeinsson, Kyle O'Brien, Tianjin Huang +8
Test-time interventions for language models can enhance factual accuracy, mitigate harmful outputs, and improve model efficiency without costly retraining. But despite a flood of n…
Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks
Jack Gallifant, Shan Chen, Pedro Moreira +7
Medical knowledge is context-dependent and requires consistent reasoning across various natural language expressions of semantically equivalent phrases. This is particularly crucia…
PolygloToxicityPrompts: Multilingual Evaluation of Neural Toxic Degeneration in Large Language Models
Devansh Jain, Priyanshu Kumar, Samuel Gehman +3
Recent advances in large language models (LLMs) have led to their extensive global deployment, and ensuring their safety calls for comprehensive and multilingual toxicity evaluatio…
TAXI: Evaluating Categorical Knowledge Editing for Language Models
Derek Powell, Walter Gerych, Thomas Hartvigsen
Humans rarely learn one fact in isolation. Instead, learning a new fact induces knowledge of other facts about the world. For example, in learning a korat is a type of cat, you als…
UniTS: A Unified Multi-Task Time Series Model
Shanghua Gao, Teddy Koker, Owen Queen +3
Although pre-trained transformers and reprogrammed text-based LLMs have shown strong performance on time series tasks, the best-performing architectures vary widely across tasks, w…
MATHWELL: Generating Educational Math Word Problems Using Teacher Annotations
Bryan R Christ, Jonathan Kropko, Thomas Hartvigsen
Math word problems are critical K-8 educational tools, but writing them is time consuming and requires extensive expertise. To be educational, problems must be solvable, have accur…
Learning under Temporal Label Noise
Sujay Nagaraj, Walter Gerych, Sana Tonekaboni +3
Many time series classification tasks, where labels vary over time, are affected by label noise that also varies over time. Such noise can cause label quality to improve, worsen, o…