We have 3 of 4 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
BenchShield is presented, a model-backed instrumentation layer for reward integrity in LLM-agent evaluation that grounds detection in a finite lifecycle model of an evaluation's reward-relevant events and achieves 96% accuracy in detecting reward hacking from infrastructure-side evidence.
This work fuse DINOv3 and CleanDIFT representations into a perception encoder and align it with RoBERTa-L, yielding a text-aligned model TDDN that preserves this perceptual advantage and leads on segmentation benchmarks among general-purpose contrastive encoders, including SigLIP.
SurakshaEval is introduced, a novel safety benchmark composed of human-written prompts spanning real-world scenarios, explicitly designed for ten major Indian languages - Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Punjabi, Tamil, and Telugu - along with English.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
