Bradley A. Malin
Bradley A. Malin has 3 papers in our library, in 2023–2026, most of them on Language models & pretraining, Evaluation & benchmarks, Knowledge graphs & ontologies; often with Jiaxin Zhang, Zhuohang Li, Caiming Xiong.
OpenAlex · ORCID · Wikidata · h-index 57 · 525 works · 11,973 citations OpenAlex, 2026-10-14
📄 3 works in our library · 🔗 Cited 26 times in our library · ⭐ Paper Stars ranking: #8502
Affiliations
Fields, topics and concepts
📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 worksBiochemistry, Genetics and Molecular Biology · 1 workHealth Informatics · 1 workMedicine · 1 workMolecular Biology · 1 work
🧭 Topics 3Research subjects and languages the work is about.Evaluation & benchmarks · 1 workLanguage models & pretraining · 1 workKnowledge graphs & ontologies · 1 work
Works by year
2020s
Papers
- SAC3: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency (2023 · 28 citations)
Black-box LMs such as ChatGPT expose no token log-probabilities, so hallucination detectors often depend on sampling and self-consistency: if repeated answers agree, the output is assumed factual. - From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models (2026 · 1 citation)
Most uncertainty quantification (UQ) work on LLMs scores an output only after it has been generated. This survey argues that such retrospective scoring does not fit multi-step reasoning, agents or alignment loops. It traces a shift in which uncertainty becomes a live control input that changes what the model does… - MHGraphBench: Knowledge Graph-Grounded Benchmarking of Mental Health Knowledge in Large Language Models (2026)
Large language models are increasingly used in mental health, but broad medical benchmarks say little about whether they hold verifiable psychiatric biomedical knowledge.
Co-authors here
Venues
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
- Workshop on Generation, Evaluation and Metrics (GEM): GEM 2026
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