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From the 1 of 15 linked papers with an AI index.

collaborators

16 papers

cs.SE2026

CoGate: Confidence-Gated Co-Decoding for Secure Code Generation

Minghao Hu, Lannan Luo, Allen Roush +1

The paper introduces CoGate, a method that uses the confidence of a security expert model to gate its influence during co-decoding for generating more secure code with large langua…

cs.AI2026

Refusal-Gated Decoding: Preserving Refusal Behavior Under High-Temperature Sampling

Phillip Howard, Xin Su, Allen Roush +2

High-temperature sampling is one of the primary mechanisms for increasing diversity in LLMs. Recent advances in truncation-based sampling techniques have helped mitigate drawbacks…

cs.CV2026

Improving Sample Diversity in Autoregressive Text-to-Image Generation via Cluster Truncation

Trang Nguyen, Shuang Wu, Runyan Tan +1

While diffusion models achieve state-of-the-art image quality for text-to-image (T2I) generation, recent work has demonstrated that they suffer from sample diversity collapse. In t…

cs.CV2026

Cross-Cultural Value Attribution in Large Vision-Language Models

Phillip Howard, Xin Su, Kathleen C. Fraser

The rapid adoption of large vision-language models (LVLMs) in recent years has been accompanied by growing fairness concerns due to their propensity to reinforce harmful societal s…

cs.CV2026

Cultural Counterfactuals: Evaluating Cultural Biases in Large Vision-Language Models with Counterfactual Examples

Phillip Howard, Xin Su, Kathleen C. Fraser

Large Vision-Language Models (LVLMs) have grown increasingly powerful in recent years, but can also exhibit harmful biases. Prior studies investigating such biases have primarily f…

cs.AI2026

Synthetic Contrastive Reasoning for Multi-Table Q&A

Ankit Pratap Singh, Xin Su, Phillip Howard

Multi-table question answering requires models to retrieve relevant evidence, link schemas, and perform compositional reasoning across relational tables. Existing multi-table Q&A r…