Papers
RouteNator: A Router-Based Multi-Modal Architecture for Generating Synthetic Training Data for Function Calling LLMs
Vibha Belavadi, Tushar Vatsa, Dewang Sultania et al.
LLM Reasoning Engine: Specialized Training for Enhanced Mathematical Reasoning
Shuguang Chen, Guang Lin
Enhancing Cross-Language Code Translation via Task-Specific Embedding Alignment in Retrieval-Augmented Generation
Manish Bhattarai, Minh Vu, Javier E. Santos et al.
Leveraging Domain Knowledge at Inference Time for LLM Translation: Retrieval versus Generation
Bryan Li, Jiaming Luo, Eleftheria Briakou et al.
GAVEL: Generative Attribute-Value Extraction Using LLMs on LLM-Augmented Datasets
Pollawat Hongwimol, Dong Sheng, Li Zhang et al.
Investigating Large Language Models for Text-to-SPARQL Generation
Jacopo D’Abramo, Andrea Zugarini, Paolo Torroni
Generating Tables from the Parametric Knowledge of Language Models
Yevgeni Berkovitch, Oren Glickman, Amit Somech et al.
Retrieval of Temporal Event Sequences from Textual Descriptions
Zefang Liu, Yinzhu Quan
Entity Retrieval for Answering Entity-Centric Questions
Hassan Shavarani, Anoop Sarkar
Evaluating Robustness of LLMs to Numerical Variations in Mathematical Reasoning
Yuli Yang, Hiroaki Yamada, Takenobu Tokunaga
Error Reflection Prompting: Can Large Language Models Successfully Understand Errors?
Jason Li, Lauren Yraola, Kevin Zhu et al.
Self Knowledge-Tracing for Tool Use (SKT-Tool): Helping LLM Agents Understand Their Capabilities in Tool Use
Joshua Vigel, Renpei Cai, Eleanor Chen et al.
Exploring Multimodal Language Models for Sustainability Disclosure Extraction: A Comparative Study
Tanay Gupta, Tushar Goel, Ishan Verma
Exploring Limitations of LLM Capabilities with Multi-Problem Evaluation
Zhengxiang Wang, Jordan Kodner, Owen Rambow
LLMs are not Zero-Shot Reasoners for Biomedical Information Extraction
Aishik Nagar, Viktor Schlegel, Thanh-Tung Nguyen et al.
Aligning Sizes of Intermediate Layers by LoRA Adapter for Knowledge Distillation
Takeshi Suzuki, Hiroaki Yamada, Takenobu Tokunaga
Bridging the Faithfulness Gap in Prototypical Models
Andrew Koulogeorge, Sean Xie, Saeed Hassanpour et al.
Does Training on Synthetic Data Make Models Less Robust?
Lingze Zhang, Ellie Pavlick
Monte Carlo Sampling for Analyzing In-Context Examples
Stephanie Schoch, Yangfeng Ji
Language-Specific Neurons Do Not Facilitate Cross-Lingual Transfer
Soumen Kumar Mondal, Sayambhu Sen, Abhishek Singhania et al.
Do Prevalent Bias Metrics Capture Allocational Harms from LLMs?
Hannah Cyberey, Yangfeng Ji, David Evans
Corrective In-Context Learning: Evaluating Self-Correction in Large Language Models
Mario Sanz-Guerrero, Katharina Von Der Wense
Reassessing Graph Linearization for Sequence-to-sequence AMR Parsing: On the Advantages and Limitations of Triple-Based
Jeongwoo Kang, Maximin Coavoux, Didier Schwab et al.
In-Context Learning on a Budget: A Case Study in Token Classification
Uri Berger, Tal Baumel, Gabriel Stanovsky