7 papers
Compliance versus Sensibility: On the Reasoning Controllability in Large Language Models
Xingwei Tan, Marco Valentino, Mahmud Elahi Akhter +3
Large Language Models (LLMs) are known to acquire reasoning capabilities through shared inference patterns in pre-training data, which are further elicited via Chain-of-Thought (Co…
LiFT: How to Enable In-Context Learning for Longitudinal Modelling
Iqra Ali, Talia Tseriotou, Mahmud Elahi Akhter +2
Longitudinal NLP tasks such as mental health monitoring and stance evolution require modeling temporally ordered text to track persistence and detect change. Such tasks also suffer…
The Alignment Bottleneck in Decomposition-Based Claim Verification
Mahmud Elahi Akhter, Federico Ruggeri, Iman Munire Bilal +2
Structured claim decomposition is often proposed as a solution for verifying complex, multi-faceted claims, yet empirical results have been inconsistent. We argue that these incons…
Fundamental Reasoning Paradigms Induce Out-of-Domain Generalization in Language Models
Mingzi Cao, Xingwei Tan, Mahmud Elahi Akhter +4
Deduction, induction, and abduction are fundamental reasoning paradigms, core for human logical thinking. Although improving Large Language Model (LLM) reasoning has attracted sign…
Enhancing Logical Reasoning in Language Models via Symbolically-Guided Monte Carlo Process Supervision
Xingwei Tan, Marco Valentino, Mahmud Akhter +2
Large language models (LLMs) have shown strong performance in many reasoning benchmarks. However, recent studies have pointed to memorization, rather than generalization, as one of…
Temporal reasoning for timeline summarisation in social media
Jiayu Song, Mahmud Elahi Akhter, Dana Atzil Slonim +1
This paper explores whether enhancing temporal reasoning capabilities in Large Language Models (LLMs) can improve the quality of timeline summarisation, the task of summarising lon…