| | --- |
| | license: mit |
| | dataset_info: |
| | - config_name: multi_turn_choice_eng |
| | features: |
| | - name: context |
| | dtype: string |
| | - name: multi_turns |
| | list: |
| | - name: answer |
| | dtype: string |
| | - name: input |
| | dtype: string |
| | - name: options |
| | sequence: string |
| | - name: id |
| | dtype: int64 |
| | splits: |
| | - name: train |
| | num_bytes: 46482955 |
| | num_examples: 58 |
| | download_size: 28590613 |
| | dataset_size: 46482955 |
| | - config_name: multi_turn_kv |
| | features: |
| | - name: id |
| | dtype: int64 |
| | - name: context |
| | dtype: string |
| | - name: multi_turns |
| | list: |
| | - name: answer |
| | dtype: string |
| | - name: input |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 20071200 |
| | num_examples: 100 |
| | download_size: 18278186 |
| | dataset_size: 20071200 |
| | - config_name: multi_turn_many_shot |
| | features: |
| | - name: context |
| | dtype: string |
| | - name: multi_turns |
| | list: |
| | - name: answer |
| | dtype: string |
| | - name: input |
| | dtype: string |
| | - name: id |
| | dtype: int64 |
| | - name: task |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 4734315 |
| | num_examples: 54 |
| | download_size: 99406 |
| | dataset_size: 4734315 |
| | - config_name: multi_turn_mf |
| | features: |
| | - name: id |
| | dtype: int64 |
| | - name: context |
| | sequence: int64 |
| | - name: multi_turns |
| | list: |
| | - name: answer |
| | dtype: int64 |
| | - name: input |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 24065100 |
| | num_examples: 100 |
| | download_size: 3766479 |
| | dataset_size: 24065100 |
| | - config_name: multi_turn_prefix_suffix |
| | features: |
| | - name: context |
| | dtype: string |
| | - name: multi_turns |
| | list: |
| | - name: answer |
| | dtype: string |
| | - name: input |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 17498600 |
| | num_examples: 100 |
| | download_size: 16417345 |
| | dataset_size: 17498600 |
| | - config_name: multi_turn_qa_chn |
| | features: |
| | - name: context |
| | dtype: string |
| | - name: multi_turns |
| | list: |
| | - name: answer |
| | dtype: string |
| | - name: input |
| | dtype: string |
| | - name: id |
| | dtype: int64 |
| | splits: |
| | - name: train |
| | num_bytes: 180437341 |
| | num_examples: 35 |
| | download_size: 115936454 |
| | dataset_size: 180437341 |
| | - config_name: multi_turn_qa_eng |
| | features: |
| | - name: context |
| | dtype: string |
| | - name: multi_turns |
| | list: |
| | - name: answer |
| | dtype: string |
| | - name: input |
| | dtype: string |
| | - name: id |
| | dtype: int64 |
| | splits: |
| | - name: train |
| | num_bytes: 58359967 |
| | num_examples: 69 |
| | download_size: 35648660 |
| | dataset_size: 58359967 |
| | - config_name: multi_turn_repoqa |
| | features: |
| | - name: context |
| | dtype: string |
| | - name: id |
| | dtype: int64 |
| | - name: multi_turns |
| | list: |
| | - name: answer |
| | dtype: string |
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| | - name: description |
| | dtype: string |
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| | dtype: int64 |
| | - name: end_line |
| | dtype: int64 |
| | - name: func |
| | dtype: string |
| | - name: global_end_byte |
| | dtype: int64 |
| | - name: global_end_line |
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| | - name: global_start_byte |
| | dtype: int64 |
| | - name: global_start_line |
| | dtype: int64 |
| | - name: input |
| | dtype: string |
| | - name: name |
| | dtype: string |
| | - name: path |
| | dtype: string |
| | - name: start_byte |
| | dtype: int64 |
| | - name: start_line |
| | dtype: int64 |
| | - name: lang |
| | dtype: string |
| | - name: repo |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 24847710 |
| | num_examples: 88 |
| | download_size: 4427455 |
| | dataset_size: 24847710 |
| | - config_name: multi_turn_repoqa_and_kv |
| | features: |
| | - name: context |
| | dtype: string |
| | - name: id |
| | dtype: int64 |
| | - name: multi_turns |
| | list: |
| | - name: answer |
| | dtype: string |
| | - name: code_ratio |
| | dtype: float64 |
| | - name: description |
| | dtype: string |
| | - name: end_byte |
| | dtype: int64 |
| | - name: end_line |
| | dtype: int64 |
| | - name: func |
| | dtype: string |
| | - name: global_end_byte |
| | dtype: int64 |
| | - name: global_end_line |
| | dtype: int64 |
| | - name: global_start_byte |
| | dtype: int64 |
| | - name: global_start_line |
| | dtype: int64 |
| | - name: input |
| | dtype: string |
| | - name: name |
| | dtype: string |
| | - name: path |
| | dtype: string |
| | - name: start_byte |
| | dtype: int64 |
| | - name: start_line |
| | dtype: int64 |
| | - name: task |
| | dtype: string |
| | - name: lang |
| | dtype: string |
| | - name: repo |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 25019328 |
| | num_examples: 88 |
| | download_size: 8583611 |
| | dataset_size: 25019328 |
| | - config_name: multi_turn_summary |
| | features: |
| | - name: context |
| | dtype: string |
| | - name: multi_turns |
| | list: |
| | - name: answer |
| | dtype: string |
| | - name: input |
| | dtype: string |
| | - name: id |
| | dtype: int64 |
| | splits: |
| | - name: train |
| | num_bytes: 28622955 |
| | num_examples: 70 |
| | download_size: 14245669 |
| | dataset_size: 28622955 |
| | - config_name: multi_turn_summary_with_needles |
| | features: |
| | - name: context |
| | dtype: string |
| | - name: multi_turns |
| | list: |
| | - name: answer |
| | dtype: string |
| | - name: input |
| | dtype: string |
| | - name: task |
| | dtype: string |
| | - name: id |
| | dtype: int64 |
| | splits: |
| | - name: train |
| | num_bytes: 28629718 |
| | num_examples: 70 |
| | download_size: 14233712 |
| | dataset_size: 28629718 |
| | - config_name: multi_turn_vt |
| | features: |
| | - name: index |
| | dtype: int64 |
| | - name: input |
| | dtype: string |
| | - name: length |
| | dtype: int64 |
| | - name: multi_turns |
| | list: |
| | - name: answer |
| | sequence: string |
| | - name: input |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 42549030 |
| | num_examples: 90 |
| | download_size: 2160077 |
| | dataset_size: 42549030 |
| | configs: |
| | - config_name: multi_turn_choice_eng |
| | data_files: |
| | - split: train |
| | path: multi_turn_choice_eng/train-* |
| | - config_name: multi_turn_kv |
| | data_files: |
| | - split: train |
| | path: multi_turn_kv/train-* |
| | - config_name: multi_turn_many_shot |
| | data_files: |
| | - split: train |
| | path: multi_turn_many_shot/train-* |
| | - config_name: multi_turn_mf |
| | data_files: |
| | - split: train |
| | path: multi_turn_mf/train-* |
| | - config_name: multi_turn_prefix_suffix |
| | data_files: |
| | - split: train |
| | path: multi_turn_prefix_suffix/train-* |
| | - config_name: multi_turn_qa_chn |
| | data_files: |
| | - split: train |
| | path: multi_turn_qa_chn/train-* |
| | - config_name: multi_turn_qa_eng |
| | data_files: |
| | - split: train |
| | path: multi_turn_qa_eng/train-* |
| | - config_name: multi_turn_repoqa |
| | data_files: |
| | - split: train |
| | path: multi_turn_repoqa/train-* |
| | - config_name: multi_turn_repoqa_and_kv |
| | data_files: |
| | - split: train |
| | path: multi_turn_repoqa_and_kv/train-* |
| | - config_name: multi_turn_summary |
| | data_files: |
| | - split: train |
| | path: multi_turn_summary/train-* |
| | - config_name: multi_turn_summary_with_needles |
| | data_files: |
| | - split: train |
| | path: multi_turn_summary_with_needles/train-* |
| | - config_name: multi_turn_vt |
| | data_files: |
| | - split: train |
| | path: multi_turn_vt/train-* |
| | --- |
| | |
| | # SCBench |
| |
|
| | [[Paper]]() |
| | [[Code]](https://github.com/microsoft/MInference/SCBench) |
| |
|
| |  |
| |
|
| | SCBench (SharedContextBench) is a comprehensive benchmark to evaluate efficient long-context methods in a KV cache-centric perspective, analyzing their performance across **the full KV cache lifecycle (generation, compression, retrieval, and loading)** in real-world scenarios where context memory (KV cache) is shared and reused across multiple requests. |
| |
|
| | ## Dataset |
| |
|
| |  |
| |
|
| | SCBench covers 12 diverse tasks that test four key long-context capabilities: string retrieval, semantic retrieval, global information processing, and multi-tasking. |
| |
|
| | ### String Retrieval |
| | - **Retr.KV**: Tests key-value lookup in large JSON objects with random, incompressible content |
| | - **Retr.Prefix-Suffix**: Evaluates finding strings with specific prefix and suffix patterns |
| | - **Retr.MultiHop**: Assesses multi-hop variable tracing capabilities in long inputs |
| |
|
| | ### Semantic Retrieval |
| | - **Code.RepoQA**: Function retrieval from large codebases based on natural language descriptions |
| | - **Language QA**: Includes English QA, Chinese QA, and multi-choice questions on long texts |
| | - Requires semantic understanding on length inputs |
| |
|
| | ### Global Information Processing |
| | - **Many-shot ICL**: Tests in-context learning with hundreds of examples |
| | - **Math.Find**: Statistical tasks on large arrays |
| | - **En.Sum**: Summarization of documents |
| | - Requires global information processing or aggregation |
| |
|
| | ### Multi-Tasking |
| | - **Mix.Sum+NIAH**: Combines summarization with needle-in-haystack search |
| | - **Mix.RepoQA+KV**: Integrates code function retrieval with key-value lookup |
| | - Requires multi-tasking or multi-step reasoning |
| |
|
| | ## Two Shared Context Modes |
| | The benchmark evaluates these tasks across two shared context modes: |
| | - **Multi-turn Mode**: Caches context within single sessions |
| | - **Multi-request Mode**: Shares context across multiple sessions |
| |
|
| | ## Compared to previous long-context benchmarks |
| |
|
| |  |
| |
|
| | Our SCBench is the first long-context benchmark that covers single-turn, multi-turn, and multi-request scenarios. In addition, our impelmentation also involves KV cache reuse techniques, thereby providing a more comprehensive analysis on the full KV cache lifecycle of efficient long-context methods. |
| |
|
| | ## Results and Findings |
| |
|
| |  |
| |
|
| | Our SCBench reveals that the following key insights: |
| |
|
| | ### Finding 1: Sub-O(n) Memory is Problematic in Multi-Request/Multi-Turn Decoding |
| | - Sparse decoding methods with sub-O(n) memory perform well on first queries but lose accuracy in subsequent requests |
| | - Methods maintaining O(n) memory with sub-O(n²) computation during pre-filling can better approximate full attention accuracy across multiple queries |
| |
|
| | ### Finding 2: Task Performance Shows Varying Decline Patterns |
| | - Sparse KV cache methods excel in tasks requiring global information processing |
| | - O(n) memory is essential for tasks involving exact match retrieval |
| |
|
| | ### Finding 3: Performance vs Compression Rate |
| | - All methods show performance degradation as compression rates increase |
| | - Sub-O(n) memory methods exhibit significant drop at 1/4 compression rate |
| | - Methods like RetrievalAttention and KIVI that maintain O(n) memory with sparse decoding show better resilience at higher compression rates |
| |
|
| | ### Finding 4: Issues with Long-Generation Scenarios |
| | - Attention distribution shifts significantly as generation length and number of rounds increase |
| | - This out-of-distribution (OOD) issue impacts performance even for O(n) memory methods |
| |
|
| | ### Finding 5: Dynamic vs Static Patterns |
| | - Dynamic sparse patterns generally outperform static patterns |
| |
|
| | ## Citation |
| |
|
| | ```bibtex |
| | @article{li2024scbench, |
| | title={SCBench: A KV cache-centric analysis of long-context methods}, |
| | author={Li, Yucheng and Jiang, Huiqiang and Wu, Qianhui and Luo, Xufang and Ahn, Surin and Zhang, Chengruidong and Abdi, Amir H and Li, Dongsheng and Gao, Jianfeng and Yang, Yuqing and Qiu, Lili}, |
| | journal={arXiv preprint arXiv:2407.02490}, |
| | year={2024} |
| | } |
| | ``` |
