Search Results for author: Elizabeth Daly

Found 11 papers, 1 papers with code

WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia

no code implementations19 Jun 2024 Yufang Hou, Alessandra Pascale, Javier Carnerero-Cano, Tigran Tchrakian, Radu Marinescu, Elizabeth Daly, Inkit Padhi, Prasanna Sattigeri

Specifically, we introduce WikiContradict, a benchmark consisting of 253 high-quality, human-annotated instances designed to assess LLM performance when augmented with retrieved passages containing real-world knowledge conflicts.

Language Modelling World Knowledge

Explaining Knock-on Effects of Bias Mitigation

no code implementations1 Dec 2023 Svetoslav Nizhnichenkov, Rahul Nair, Elizabeth Daly, Brian Mac Namee

In this paper, we aim to characterise impacted cohorts when mitigation interventions are applied.

Fairness

Iterative Reward Shaping using Human Feedback for Correcting Reward Misspecification

1 code implementation30 Aug 2023 Jasmina Gajcin, James McCarthy, Rahul Nair, Radu Marinescu, Elizabeth Daly, Ivana Dusparic

Our approach allows the user to provide trajectory-level feedback on agent's behavior during training, which can be integrated as a reward shaping signal in the following training iteration.

Reinforcement Learning (RL)

Leveraging Explanations in Interactive Machine Learning: An Overview

no code implementations29 Jul 2022 Stefano Teso, Öznur Alkan, Wolfang Stammer, Elizabeth Daly

Explanations have gained an increasing level of interest in the AI and Machine Learning (ML) communities in order to improve model transparency and allow users to form a mental model of a trained ML model.

BIG-bench Machine Learning

Boolean Decision Rules for Reinforcement Learning Policy Summarisation

no code implementations18 Jul 2022 James McCarthy, Rahul Nair, Elizabeth Daly, Radu Marinescu, Ivana Dusparic

Explainability of Reinforcement Learning (RL) policies remains a challenging research problem, particularly when considering RL in a safety context.

reinforcement-learning Reinforcement Learning (RL)

Contrastive Explanations for Comparing Preferences of Reinforcement Learning Agents

no code implementations17 Dec 2021 Jasmina Gajcin, Rahul Nair, Tejaswini Pedapati, Radu Marinescu, Elizabeth Daly, Ivana Dusparic

In complex tasks where the reward function is not straightforward and consists of a set of objectives, multiple reinforcement learning (RL) policies that perform task adequately, but employ different strategies can be trained by adjusting the impact of individual objectives on reward function.

Autonomous Driving reinforcement-learning +1

Designing Machine Learning Pipeline Toolkit for AutoML Surrogate Modeling Optimization

no code implementations2 Jul 2021 Paulito P. Palmes, Akihiro Kishimoto, Radu Marinescu, Parikshit Ram, Elizabeth Daly

The pipeline optimization problem in machine learning requires simultaneous optimization of pipeline structures and parameter adaptation of their elements.

AutoML BIG-bench Machine Learning +1

User Profiling from Reviews for Accurate Time-Based Recommendations

no code implementations15 Jun 2020 Oznur Alkan, Elizabeth Daly

However, temporal aspects of a user profile may not always be explicitly available and so we may need to infer this information from available resources.

Recommendation Systems

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