24 citations · 30 across the 6 of their papers we have counts for
6 papers
A Benchmark for Deep Information Synthesis
Debjit Paul, Daniel Murphy, Milan Gritta +14
Large language model (LLM)-based agents are increasingly used to solve complex tasks involving tool use, such as web browsing, code execution, and data analysis. However, current e…
Memento: Fine-tuning LLM Agents without Fine-tuning LLMs
Huichi Zhou, Yihang Chen, Siyuan Guo +8
In this paper, we introduce a novel learning paradigm for Adaptive Large Language Model (LLM) agents that eliminates the need for fine-tuning the underlying LLMs. Existing approach…
Text-to-Code Generation with Modality-relative Pre-training
Fenia Christopoulou, Guchun Zhang, Gerasimos Lampouras
Large pre-trained language models have recently been expanded and applied to programming language tasks with great success, often through further pre-training of a strictly-natural…
A Systematic Study of Performance Disparities in Multilingual Task-Oriented Dialogue Systems
Songbo Hu, Han Zhou, Moy Yuan +5
Achieving robust language technologies that can perform well across the world's many languages is a central goal of multilingual NLP. In this work, we take stock of and empirically…
Multi3WOZ: A Multilingual, Multi-Domain, Multi-Parallel Dataset for Training and Evaluating Culturally Adapted Task-Oriented Dialog Systems
Songbo Hu, Han Zhou, Mete Hergul +5
Creating high-quality annotated data for task-oriented dialog (ToD) is known to be notoriously difficult, and the challenges are amplified when the goal is to create equitable, cul…
PanGu-Coder: Program Synthesis with Function-Level Language Modeling
Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta +19
We present PanGu-Coder, a pretrained decoder-only language model adopting the PanGu-Alpha architecture for text-to-code generation, i.e. the synthesis of programming language solut…