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cs.CL2024
Pre-Training Multimodal Hallucination Detectors with Corrupted Grounding Data
Spencer Whitehead, Jacob Phillips, Sean Hendryx
Multimodal language models can exhibit hallucinations in their outputs, which limits their reliability. The ability to automatically detect these errors is important for mitigating…
cs.CL2024
Learning Goal-Conditioned Representations for Language Reward Models
Vaskar Nath, Dylan Slack, Jeff Da +4
Techniques that learn improved representations via offline data or self-supervised objectives have shown impressive results in traditional reinforcement learning (RL). Nevertheless…