Yireun Kim, Jiyeon Kim, Eunbi Choi, Soyoung Yoon, Seung-Won Hwang, Hyeongu Yun
We lifted 5 functions out of this paper's own repositories and ran 3 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| soyoung97/ListT5 | — | 2 of 4 |
| copy not recorded | — | 1 of 1 |
| Function | Status | Where it lives |
|---|---|---|
| EncoderWrapper | Ran | soyoung97/ListT5/train_code/models/FiDT5.py pointer only (licence: NONE) · get_code("4c281a5a3d35717b") |
| FiDT5 | Ran | soyoung97/ListT5/train_code/models/FiDT5.py pointer only (licence: NONE) · get_code("d5799a134c8250b1") |
| cross_attention_forward | Ran | this paper's copy was not recorded; identical code first harvested from andyzoujm/autocast pointer only · get_code("6bef6bdd6eb44070") |
| CheckpointWrapper | Not yet run | soyoung97/ListT5/train_code/models/FiDT5.py pointer only (licence: NONE) · get_code("f3d610d21ffa004a") |
| apply_checkpoint_wrapper | Not yet run | soyoung97/ListT5/train_code/models/FiDT5.py pointer only (licence: NONE) · get_code("f3acdcf7a36eb548") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
We propose LISTT5, a novel reranking approach based on Fusion-in-Decoder (FiD) that handles multiple candidate passages at both train and inference time. We also introduce an efficient inference framework for listwise ranking based on m-ary tournament sort with output caching. We evaluate and compare our model on the BEIR benchmark for zero-shot retrieval task, demonstrating that LISTT5 (1) outperforms the state-of-the-art RankT5 baseline with a notable +1.3 gain in the average NDCG@10 score, (2) has an efficiency comparable to pointwise ranking models and surpasses the efficiency of previous listwise ranking models, and (3) overcomes the lost-in-the-middle problem of previous listwise rerankers. Our code, model checkpoints, and the evaluation framework are fully open-sourced at https: //github.com/soyoung97/ListT5.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2402.15838")
get_code_for_paper("2402.15838")
have("2402.15838")
Connect an agent — have() is free.