6 papers
No Shortcuts to Culture: Indonesian Multi-hop Question Answering for Complex Cultural Understanding
Vynska Amalia Permadi, Xingwei Tan, Nafise Sadat Moosavi +1
Understanding culture requires reasoning across context, tradition, and implicit social knowledge, far beyond recalling isolated facts. Yet most culturally focused question answeri…
Fine-Tuning on Noisy Instructions: Effects on Generalization and Performance
Ahmed Alajrami, Xingwei Tan, Nikolaos Aletras
Instruction-tuning plays a vital role in enhancing the task-solving abilities of large language models (LLMs), improving their usability in generating helpful responses on various…
Can Confidence Estimates Decide When Chain-of-Thought Is Necessary for LLMs?
Samuel Lewis-Lim, Xingwei Tan, Zhixue Zhao +1
Chain-of-thought (CoT) prompting is a common technique for improving the reasoning abilities of large language models (LLMs). However, extended reasoning is often unnecessary and s…
IntSR: An Integrated Generative Framework for Search and Recommendation
Huimin Yan, Longfei Xu, Junjie Sun +6
Generative recommendation has emerged as a promising paradigm, demonstrating remarkable results in both academic benchmarks and industrial applications. However, existing systems p…
Analysing Chain of Thought Dynamics: Active Guidance or Unfaithful Post-hoc Rationalisation?
Samuel Lewis-Lim, Xingwei Tan, Zhixue Zhao +1
Recent work has demonstrated that Chain-of-Thought (CoT) often yields limited gains for soft-reasoning problems such as analytical and commonsense reasoning. CoT can also be unfait…
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…