6 papers
Oracle-RLAIF: An Improved Fine-Tuning Framework for Multi-modal Video Models using Reinforcement Learning from Ranking Feedback
Derek Shi, Ruben Glatt, Christine Klymko +5
Recent advances in large video-language models (VLMs) rely on extensive fine-tuning techniques that strengthen alignment between textual and visual comprehension. Leading pipelines…
VERIRAG: A Post-Retrieval Auditing of Scientific Study Summaries
Shubham Mohole, Hongjun Choi, Shusen Liu +6
Can democratized information gatekeepers and community note writers effectively decide what scientific information to amplify? Lacking domain expertise, such gatekeepers rely on au…
A Generalizable Rhetorical Strategy Annotation Model Using LLM-based Debate Simulation and Labelling
Shiyu Ji, Farnoosh Hashemi, Joice Chen +9
Rhetorical strategies are central to persuasive communication, from political discourse and marketing to legal argumentation. However, analysis of rhetorical strategies has been li…
SIFOTL: A Principled, Statistically-Informed Fidelity-Optimization Method for Tabular Learning
Shubham Mohole, Sainyam Galhotra
Identifying the factors driving data shifts in tabular datasets is a significant challenge for analysis and decision support systems, especially those focusing on healthcare. Priva…
VeriMinder: Mitigating Analytical Vulnerabilities in NL2SQL
Shubham Mohole, Sainyam Galhotra
Application systems using natural language interfaces to databases (NLIDBs) have democratized data analysis. This positive development has also brought forth an urgent challenge to…
Communication is All You Need: Persuasion Dataset Construction via Multi-LLM Communication
Weicheng Ma, Hefan Zhang, Ivory Yang +8
Large Language Models (LLMs) have shown proficiency in generating persuasive dialogue, yet concerns about the fluency and sophistication of their outputs persist. This paper presen…