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cs.CL2025
Distillation versus Contrastive Learning: How to Train Your Rerankers
Zhichao Xu, Zhiqi Huang, Shengyao Zhuang +1
Training effective text rerankers is crucial for information retrieval. Two strategies are widely used: contrastive learning (optimizing directly on ground-truth labels) and knowle…
cs.CL2025★ 1 cited
Found in Translation: Measuring Multilingual LLM Consistency as Simple as Translate then Evaluate
Ashim Gupta, Maitrey Mehta, Zhichao Xu +1
Large language models (LLMs) provide detailed and impressive responses to queries in English. However, are they really consistent at responding to the same query in other languages…
cs.CL2025
Test-Time Scaling with Repeated Sampling Improves Multilingual Text Generation
Ashim Gupta, Vivek Srikumar
Inference-time scaling via repeated sampling has shown promise in reasoning tasks, but its effectiveness in multilingual generation remains underexplored. We evaluate this approach…