2 papers
cs.CV2026
ENTRAP-VL: A Taxonomic Probe for Dual Contextual Entrainment in Vision-Language Models
Karan Goyal, Afreen Hossain, Debojyoti Das +1
Contextual entrainment is the tendency of a model to let auxiliary context in its input pull its output, independently of whether that context is relevant, true, or even meaningful…
cs.AI2026
Litmus: Zero-Label, Code-Driven Metric Specification for Evaluating AI Systems
Prajjwal Gupta, Prasang Gupta, Vishal Bhutani +4
As agentic LLM systems move from prototypes to deployment across increasingly diverse domains, evaluating them has become both more important and more difficult. The challenge is n…