collaborators

13 papers

cs.LG2026

GraphER: An Efficient Graph-Based Enrichment and Reranking Method for Retrieval-Augmented Generation

Ruizhong Miao, Yuying Wang, Rongguang Wang +4

Semantic search in retrieval-augmented generation (RAG) systems is often insufficient for complex information needs, particularly when relevant evidence is scattered across multipl…

cs.CV2026

Do Image-Text Metrics Respect Semantic Invariances?

Amit Agarwal, Hitesh Laxmichand Patel, Meizhu Liu +9

Reference-free image-to-text evaluators are now standard for scoring image-caption alignment, yet it is unclear whether they respect semantic invariances. We present an invariance…

cs.CL2026

Robust Audio-Text Retrieval via Cross-Modal Attention and Hybrid Loss

Meizhu Liu, Matthew Rowe, Amit Agarwal +8

Audio-text retrieval enables semantic alignment between audio content and natural language queries, supporting applications in multimedia search, accessibility, and surveillance. H…

cs.CL2026

SPENCE: A Syntactic Probe for Detecting Contamination in NL2SQL Benchmarks

Mohammadtaher Safarzadeh, Hitesh Laxmichand Patel, Afshin Orojlooyjadid +2

Large language models (LLMs) have achieved strong performance on natural language to SQL (NL2SQL) benchmarks, yet their reported accuracy may be inflated by contamination from benc…

cs.AI2026

When Vision-Language Models Judge Without Seeing: Exposing Informativeness Bias

Xiaohan Zou, Roshan Sridhar, Mohammadtaher Safarzadeh +1

The reliability of VLM-as-a-Judge is critical for the automatic evaluation of vision-language models (VLMs). Despite recent progress, our analysis reveals that VLM-as-a-Judge often…

cs.AI2026

PAR-RAG: Planned Active Retrieval and Reasoning for Multi-Hop Question Answering

Xingyu Li, Rongguang Wang, Yuying Wang +5

Large language models (LLMs) remain brittle on multi-hop question answering (MHQA), where answering requires combining evidence across documents through retrieval and reasoning. It…