9 papers
LLMs Underperform Graph-Based Parsers on Supervised Relation Extraction for Complex Graphs
Paolo Gajo, Domenic Rosati, Hassan Sajjad +1
Relation extraction represents a fundamental component in the process of creating knowledge graphs, among other applications. Large language models (LLMs) have been adopted as a pr…
Dependency Parsing is More Parameter-Efficient with Normalization
Paolo Gajo, Domenic Rosati, Hassan Sajjad +1
Dependency parsing is the task of inferring natural language structure, often approached by modeling word interactions via attention through biaffine scoring. This mechanism works…
Resolving Lexical Bias in Model Editing
Hammad Rizwan, Domenic Rosati, Ga Wu +1
Model editing aims to modify the outputs of large language models after they are trained. Previous approaches have often involved direct alterations to model weights, which can res…
Content-aware rankings: a new approach to rankings in scholarship
Sean C. Rife, Joshua M. Nicholson, Beatriz Bosques +3
Entity rankings (e.g., institutions, journals) are a core component of academia and related industries. Existing approaches to institutional rankings have relied on a variety of da…
Evaluating Defences against Unsafe Feedback in RLHF
Domenic Rosati, Giles Edkins, Harsh Raj +5
While there has been progress towards aligning Large Language Models (LLMs) with human values and ensuring safe behaviour at inference time, safety guards can easily be removed whe…
Improving Consistency in Large Language Models through Chain of Guidance
Harsh Raj, Vipul Gupta, Domenic Rosati +1
Consistency is a fundamental dimension of trustworthiness in Large Language Models (LLMs). For humans to be able to trust LLM-based applications, their outputs should be consistent…