64 citations · 484 across the 23 of their papers we have counts for
6 papers · 1 filter
Evaluating Rubric Generation with Interventional Transfer
Erik Skalnes, Layne C. Price, Raviteja Anantha +1
Instance-specific rubrics are common in AI benchmarks where reliable evaluation requires specific expert knowledge. This approach is difficult to scale, prompting research into the…
Align-RAG: Alignment Is All You Need for TSFM In-Context Learning
Mohammad Asadi, Soheil Hor, Bardiya Akhbari +6
Retrieval-augmented forecasting promises to adapt frozen Time Series Foundation Models (TSFMs) to new domains without fine-tuning, but recent methods typically rely on learned fusi…
NanoFlux: Adversarial Dual-LLM Evaluation and Distillation For Multi-Domain Reasoning
Raviteja Anantha, Soheil Hor, Teodor Nicola Antoniu +1
We present NanoFlux, a novel adversarial framework for generating targeted training data to improve LLM reasoning, where adversarially-generated datasets containing fewer than 200…
Activity Classification Using Unsupervised Domain Transfer from Body Worn Sensors
Chaitra Hedge, Gezheng Wen, Layne C. Price
Activity classification has become a vital feature of wearable health tracking devices. As innovation in this field grows, wearable devices worn on different parts of the body are…
Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information
Yulun Wu, Robert A. Barton, Zichen Wang +5
Predicting the responses of a cell under perturbations may bring important benefits to drug discovery and personalized therapeutics. In this work, we propose a novel graph variatio…
Discovering Invariances in Healthcare Neural Networks
Mohammad Taha Bahadori, Layne C. Price
We study the invariance characteristics of pre-trained predictive models by empirically learning transformations on the input that leave the prediction function approximately uncha…