24 citations · 34 across the 12 of their papers we have counts for
14 papers
Super Weights in LLMs and the Failure of Selective Training
Shreyas Subramanian, Adewale Akinfaderin, Akarsha Sehwag
Recent work identified Super Weights, individual parameters whose removal degrades model performance by orders of magnitude. We show that this degradation due to pruning Super Weig…
FregeLogic at SemEval 2026 Task 11: A Hybrid Neuro-Symbolic Architecture for Content-Robust Syllogistic Validity Prediction
Adewale Akinfaderin, Nafi Diallo
We present FregeLogic, a hybrid neuro-symbolic system for SemEval-2026 Task 11 (Subtask 1), which addresses syllogistic validity prediction while reducing content effects on predic…
Keyword search is all you need: Achieving RAG-Level Performance without vector databases using agentic tool use
Shreyas Subramanian, Adewale Akinfaderin, Yanyan Zhang +4
While Retrieval-Augmented Generation (RAG) has proven effective for generating accurate, context-based responses based on existing knowledge bases, it presents several challenges i…
VERAFI: Verified Agentic Financial Intelligence through Neurosymbolic Policy Generation
Adewale Akinfaderin, Shreyas Subramanian
Financial AI systems suffer from a critical blind spot: while Retrieval-Augmented Generation (RAG) excels at finding relevant documents, language models still generate calculation…
Plan-and-Write: Structure-Guided Length Control for LLMs without Model Retraining
Adewale Akinfaderin, Shreyas Subramanian, Akarsha Sehwag
Length control in Large Language Models (LLMs) is a crucial but under-addressed challenge, with applications ranging from voice interfaces requiring concise responses to research s…
User-Based Sequential Modeling with Transformer Encoders for Insider Threat Detection
Mohamed Elbasheer, Adewale Akinfaderin
Insider threat detection presents unique challenges due to the authorized status of malicious actors and the subtlety of anomalous behaviors. Existing machine learning methods ofte…
Temporal Analysis of Climate Policy Discourse: Insights from Dynamic Embedded Topic Modeling
Rafiu Adekoya Badekale, Adewale Akinfaderin
Understanding how policy language evolves over time is critical for assessing global responses to complex challenges such as climate change. Temporal analysis helps stakeholders, i…
AI-Driven Climate Policy Scenario Generation for Sub-Saharan Africa
Rafiu Adekoya Badekale, Adewale Akinfaderin
Climate policy scenario generation and evaluation have traditionally relied on integrated assessment models (IAMs) and expert-driven qualitative analysis. These methods enable stak…
MasakhaNER: Named Entity Recognition for African Languages
David Ifeoluwa Adelani, Jade Abbott, Graham Neubig +58
We take a step towards addressing the under-representation of the African continent in NLP research by creating the first large publicly available high-quality dataset for named en…
Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages
Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila +45
Research in NLP lacks geographic diversity, and the question of how NLP can be scaled to low-resourced languages has not yet been adequately solved. "Low-resourced"-ness is a compl…
HausaMT v1.0: Towards English-Hausa Neural Machine Translation
Adewale Akinfaderin
Neural Machine Translation (NMT) for low-resource languages suffers from low performance because of the lack of large amounts of parallel data and language diversity. To contribute…
Predicting and Analyzing Law-Making in Kenya
Oyinlola Babafemi, Adewale Akinfaderin
Modelling and analyzing parliamentary legislation, roll-call votes and order of proceedings in developed countries has received significant attention in recent years. In this paper…
Masakhane -- Machine Translation For Africa
Iroro Orife, Julia Kreutzer, Blessing Sibanda +22
Africa has over 2000 languages. Despite this, African languages account for a small portion of available resources and publications in Natural Language Processing (NLP). This is du…
NASS-AI: Towards Digitization of Parliamentary Bills using Document Level Embedding and Bidirectional Long Short-Term Memory
Adewale Akinfaderin, Olamilekan Wahab
There has been several reports in the Nigerian and International media about the Senators and House of Representative Members of the Nigerian National Assembly (NASS) being the hig…