Papers by Sue Hyun Park

2 papers
Can Large Language Models Keep Up? Benchmarking Online Adaptation to Continual Knowledge Streams (2026.acl-long)

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Challenge: Existing models and agentic memory systems fail to adapt robustly to OAKS, demonstrating delays in state-tracking and susceptibility to distraction within streaming environments.
Approach: They propose a benchmark to evaluate models' ability to adapt to changing knowledge over streaming . they use two datasets to analyze how facts evolve over time .
Outcome: The proposed benchmark evaluates models in an online adaptation setting over streaming, continually updating knowledge.
The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models (2025.naacl-long)

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Challenge: a recent study evaluated language models using abstract evaluation criteria that lack the flexibility and granularity of human assessment.
Approach: They propose a benchmark to evaluate nine distinct language models' capabilities . they use instance-specific evaluation criteria to mirror human evaluation .
Outcome: The proposed benchmark evaluates nine distinct capabilities of language models across 77 tasks.

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