@inproceedings{dutta-etal-2025-assessing,
    title = "Assessing the Limits of In-Context Learning beyond Functions using Partially Ordered Relation",
    author = "Dutta, Debanjan  and
      Ansari, Faizanuddin  and
      Das, Swagatam",
    editor = "Inui, Kentaro  and
      Sakti, Sakriani  and
      Wang, Haofen  and
      Wong, Derek F.  and
      Bhattacharyya, Pushpak  and
      Banerjee, Biplab  and
      Ekbal, Asif  and
      Chakraborty, Tanmoy  and
      Singh, Dhirendra Pratap",
    booktitle = "Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics",
    month = dec,
    year = "2025",
    address = "Mumbai, India",
    publisher = "The Asian Federation of Natural Language Processing and The Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.ijcnlp-long.50/",
    pages = "900--918",
    ISBN = "979-8-89176-298-5",
    abstract = "Generating rational and generally accurate responses to tasks, often accompanied by example demonstrations, highlights Large Language Model{'}s (LLM{'}s) remarkable In-Context Learning (ICL) capabilities without requiring updates to the model{'}s parameter space. Despite having an ongoing exploration focused on the inference from a document-level concept, its behavior in learning well-defined functions or relations in context needs a careful investigation. In this article, we present the performance of ICL on partially ordered relation by introducing the notion of inductively increasing complexity in prompts. In most cases, the saturated performance of the chosen metric indicates that while ICL offers some benefits, its effectiveness remains constrained as we increase the complexity in the prompts even in presence of sufficient demonstrative examples. The behavior is evident from our empirical findings and has further been theoretically justified in term of its implicit optimization process.The code is available here."
}