activity
20222024
most citedEnhancing Large Language Models with Climate Resources

8 citations · 25 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CL2024★ 2 cited

Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering

Tobias Schimanski, Jingwei Ni, Mathias Kraus +2

Advances towards more faithful and traceable answers of Large Language Models (LLMs) are crucial for various research and practical endeavors. One avenue in reaching this goal is b…

cs.LG2023★ 2 cited

ClimateBERT-NetZero: Detecting and Assessing Net Zero and Reduction Targets

Tobias Schimanski, Julia Bingler, Camilla Hyslop +2

Public and private actors struggle to assess the vast amounts of information about sustainability commitments made by various institutions. To address this problem, we create a nov…

cs.CL2023★ 6 cited

CHATREPORT: Democratizing Sustainability Disclosure Analysis through LLM-based Tools

Jingwei Ni, Julia Bingler, Chiara Colesanti-Senni +10

In the face of climate change, are companies really taking substantial steps toward more sustainable operations? A comprehensive answer lies in the dense, information-rich landscap…

cs.CL2023★ 3 cited

Paradigm Shift in Sustainability Disclosure Analysis: Empowering Stakeholders with CHATREPORT, a Language Model-Based Tool

Jingwei Ni, Julia Bingler, Chiara Colesanti-Senni +10

This paper introduces a novel approach to enhance Large Language Models (LLMs) with expert knowledge to automate the analysis of corporate sustainability reports by benchmarking th…

cs.CL2023

chatClimate: Grounding Conversational AI in Climate Science

Saeid Ashraf Vaghefi, Qian Wang, Veruska Muccione +8

Large Language Models (LLMs) have made significant progress in recent years, achieving remarkable results in question-answering tasks (QA). However, they still face two major chall…

cs.CL2023★ 8 cited

Enhancing Large Language Models with Climate Resources

Mathias Kraus, Julia Anna Bingler, Markus Leippold +5

Large language models (LLMs) have significantly transformed the landscape of artificial intelligence by demonstrating their ability in generating human-like text across diverse top…

cs.CL2022

Environmental Claim Detection

Dominik Stammbach, Nicolas Webersinke, Julia Anna Bingler +2

To transition to a green economy, environmental claims made by companies must be reliable, comparable, and verifiable. To analyze such claims at scale, automated methods are needed…

cs.CL2022★ 4 cited

Towards Climate Awareness in NLP Research

Daniel Hershcovich, Nicolas Webersinke, Mathias Kraus +2

The climate impact of AI, and NLP research in particular, has become a serious issue given the enormous amount of energy that is increasingly being used for training and running co…