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Interpreting the Latent Structure of Operator Precedence in Language Models
Dharunish Yugeswardeenoo, Harshil Nukala, Ved Shah +4
Large Language Models (LLMs) have demonstrated impressive reasoning capabilities but continue to struggle with arithmetic tasks. Prior works largely focus on outputs or prompting s…
DuoLens: A Framework for Robust Detection of Machine-Generated Multilingual Text and Code
Shriyansh Agrawal, Aidan Lau, Sanyam Shah +4
The prevalence of Large Language Models (LLMs) for generating multilingual text and source code has only increased the imperative for machine-generated content detectors to be accu…
ERGO: Entropy-guided Resetting for Generation Optimization in Multi-turn Language Models
Haziq Mohammad Khalid, Athikash Jeyaganthan, Timothy Do +4
Large Language Models (LLMs) suffer significant performance degradation in multi-turn conversations when information is presented incrementally. Given that multi-turn conversations…
Probe-Rewrite-Evaluate: A Workflow for Reliable Benchmarks and Quantifying Evaluation Awareness
Lang Xiong, Nishant Bhargava, Jianhang Hong +4
Large Language Models (LLMs) often exhibit significant behavioral shifts when they perceive a change from a real-world deployment context to a controlled evaluation setting, a phen…
Adaptive Originality Filtering: Rejection Based Prompting and RiddleScore for Culturally Grounded Multilingual Riddle Generation
Duy Le, Kent Ziti, Evan Girard-Sun +4
Language models are increasingly tested on multilingual creativity, demanding culturally grounded, abstract generations. Standard prompting methods often produce repetitive or shal…
Pruning for Performance: Efficient Idiom and Metaphor Classification in Low-Resource Konkani Using mBERT
Timothy Do, Pranav Saran, Harshita Poojary +4
In this paper, we address the persistent challenges that figurative language expressions pose for natural language processing (NLP) systems, particularly in low-resource languages…