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Found 11 papers, 4 papers with code
LLM for Comparative Narrative Analysis
In this paper, we conducted a Multi-Perspective Comparative Narrative Analysis (CNA) on three prominent LLMs: GPT-3. 5, PaLM2, and Llama2.
LLM for Complex Reasoning Task: An Exploratory Study in Fermi Problems
Comparative experiments confirmed this hypothesis, demonstrating that LLMs performed better on standard FPs in terms of both accuracy and efficiency.
OrdRankBen: A Novel Ranking Benchmark for Ordinal Relevance in NLP
The evaluation of ranking tasks remains a significant challenge in natural language processing (NLP), particularly due to the lack of direct labels for results in real-world scenarios.
Prompting a Weighting Mechanism into LLM-as-a-Judge in Two-Step: A Case Study
While Large Language Models (LLMs) have emerged as promising tools for evaluating Natural Language Generation (NLG) tasks, their effectiveness is limited by their inability to appropriately weigh the importance of different topics, often overemphasizing minor details while undervaluing critical information, leading to misleading assessments.
Towards Effective Authorship Attribution: Integrating Class-Incremental Learning
However, current AA benchmarks commonly overlook this uniqueness and frame the problem as a closed-world classification, assuming a fixed number of authors throughout the system's lifespan and neglecting the inclusion of emerging new authors.
Investigating Annotator Bias in Large Language Models for Hate Speech Detection
This paper serves as a crucial resource, guiding researchers and practitioners in harnessing the potential of LLMs for data annotation, thereby fostering advancements in this critical field.
OffensiveLang: A Community Based Implicit Offensive Language Dataset
Firstly, the existing datasets primarily rely on the collection of texts containing explicit offensive keywords, making it challenging to capture implicitly offensive contents that are devoid of these keywords.
LLMs as Meta-Reviewers' Assistants: A Case Study
One of the most important yet onerous tasks in the academic peer-reviewing process is composing meta-reviews, which involves assimilating diverse opinions from multiple expert peers, formulating one's self-judgment as a senior expert, and then summarizing all these perspectives into a concise holistic overview to make an overall recommendation.
TELeR: A General Taxonomy of LLM Prompts for Benchmarking Complex Tasks
However, conducting such benchmarking studies is challenging because of the large variations in LLMs' performance when different prompt types/styles are used and different degrees of detail are provided in the prompts.
Zero-Shot Multi-Label Topic Inference with Sentence Encoders
Sentence encoders have indeed been shown to achieve superior performances for many downstream text-mining tasks and, thus, claimed to be fairly general.
Joint Upper & Lower Bound Normalization for IR Evaluation
Experiments on two different data-sets with eight Learning-to-Rank (LETOR) methods demonstrate the following properties of the new LB normalized metric: 1) Statistically significant differences (between two methods) in terms of original metric no longer remain statistically significant in terms of Upper Lower (UL) Bound normalized version and vice-versa, especially for uninformative query-sets.
