1 citations · 1 across the 4 of their papers we have counts for
4 papers
Measuring Semantic Progress in Multi-turn Dialogue via Information Gain
Paul He, Shiva Kasiviswanathan, Dominik Janzing
Evaluating multi-turn dialogue is challenging because quality emerges across turns rather than within individual responses. We focus on a key dimension of information-seeking dialo…
Uncovering Hidden Correctness in LLM Causal Reasoning via Symbolic Verification
Paul He, Yinya Huang, Mrinmaya Sachan +1
Large language models (LLMs) are increasingly being applied to tasks that involve causal reasoning. However, current benchmarks often rely on string matching or surface-level metri…
Global Consistency Repair for Natural-Language Claim Sets
Paul He, Elke Kirschbaum, Shiva Kasiviswanathan
NLP systems increasingly aggregate claims from retrieved passages, documents, and generated reasoning steps. Yet current factuality methods mostly verify claims individually or com…
Pointwise Mutual Information as a Performance Gauge for Retrieval-Augmented Generation
Tianyu Liu, Jirui Qi, Paul He +3
Recent work suggests that large language models enhanced with retrieval-augmented generation are easily influenced by the order, in which the retrieved documents are presented to t…