12 papers
EmpiriGraph-Psy: A Dataset and LLM Pipeline for Extracting Empirical Relation Graphs from Psychology Abstracts
Danqin Zhao, Yicun Liu, Xingwei Tan +1
Existing scientific relation extraction benchmarks mainly target domains such as computer science, where entities are tasks, methods, datasets, materials, or metrics. This leaves a…
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…
Where does output diversity collapse in post-training?
Constantinos Karouzos, Xingwei Tan, Nikolaos Aletras
Post-trained language models produce less varied outputs than their base counterparts. This output diversity collapse undermines inference-time scaling methods that rely on varied…
DiPO: Disentangled Perplexity Policy Optimization for Fine-grained Exploration-Exploitation Trade-Off
Xiaofan Li, Ming Yang, Zhiyuan Ma +9
Reinforcement Learning with Verifiable Rewards (RLVR) has catalyzed significant advances in the reasoning capabilities of Large Language Models (LLMs). However, effectively managin…
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…
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…