Apr 2, 2024 · We evaluate on 15 long-context LLMs and find that they perform well on less challenging classification tasks with smaller label space and ...
Dec 31, 2023 · We evaluate 13 long-context LLMs on our benchmarks. We find that the long-context LLMs perform relatively well on less challenging tasks with ...
We created LongICLBench to conduct comprehensive evaluations of Large Language Models (LLMs) on extreme-label classification challenges with in-context ...
Apr 2, 2024 · This study introduces a specialized benchmark (LIConBench) focusing on long in-context learning within the realm of extreme-label classification ...
We introduce a benchmark (LongICLBench) for long in-context learning in extreme-label classification using six datasets with 28 to 174 classes and input lengths ...
Apr 2, 2024 · A benchmark for long in-context learning in extreme-label classification using six datasets with 28 to 174 classes and input lengths from 2K ...
Apr 10, 2024 · This approach challenges LLMs to process and understand extensive inputs to accurately predict from a vast label space, as in tasks like ...
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Apr 3, 2024 · Long Context LLMs Struggle with Long In-Context Learning Finds that after evaluating 13 long-context LLMs on long in-context learning the LLMs ...
Apr 3, 2024 · Long-context LLMs Struggle with Long In-context Learning Suggests a notable gap in current LLM capabilities for processing and understanding ...
Apr 24, 2024 · Long-context LLMs perform relatively well on less challenging tasks with shorter demonstration lengths by effectively utilising the long context ...