Richard Johansson, Mehrdad Farahani
We lifted 17 functions out of this paper's own repositories and ran 14 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 |
|---|---|---|
| m3hrdadfi/rag-memory-interplay | canonical | 14 of 17 |
| Function | Status | Where it lives |
|---|---|---|
| all_gather | Ran | m3hrdadfi/rag-memory-interplay/src/atlas/dist_utils.py pointer only (licence: NONE) · get_code("59ea1420911ddd97") |
| deserialize_listdocs | Ran | m3hrdadfi/rag-memory-interplay/src/atlas/index.py pointer only (licence: NONE) · get_code("a47d716bd6cdafab") |
| dict_to_args_list | Ran | m3hrdadfi/rag-memory-interplay/src/utils.py pointer only (licence: NONE) · get_code("fbd05734c3267af1") |
| em | Ran | m3hrdadfi/rag-memory-interplay/src/atlas/evaluation.py pointer only (licence: NONE) · get_code("38c3b1ee62b65838") |
| encode_passages | Ran | m3hrdadfi/rag-memory-interplay/src/atlas/atlas.py pointer only (licence: NONE) · get_code("e4a21bc7a716330c") |
| f1 | Ran | m3hrdadfi/rag-memory-interplay/src/atlas/evaluation.py pointer only (licence: NONE) · get_code("5e2f0b798a3d70d2") |
| gather_wgrad | Ran | m3hrdadfi/rag-memory-interplay/src/atlas/dist_utils.py pointer only (licence: NONE) · get_code("094781db771538f0") |
| isfloat | Ran | m3hrdadfi/rag-memory-interplay/src/causal_trace.py pointer only (licence: NONE) · get_code("bb1041c0bde2033c") |
| normalize_answer | Ran | m3hrdadfi/rag-memory-interplay/src/atlas/evaluation.py pointer only (licence: NONE) · get_code("6205dd62c2627dde") |
| parse_attributes | Ran | m3hrdadfi/rag-memory-interplay/src/causal_trace.py pointer only (licence: NONE) · get_code("c268b2c0da209fa9") |
| read_json_file | Ran | m3hrdadfi/rag-memory-interplay/src/utils.py pointer only (licence: NONE) · get_code("07609cc6c26d3a72") |
| select_crossattention_scores | Ran | m3hrdadfi/rag-memory-interplay/src/atlas/atlas.py pointer only (licence: NONE) · get_code("c4bca944bda65eb2") |
| serialize_listdocs | Ran | m3hrdadfi/rag-memory-interplay/src/atlas/index.py pointer only (licence: NONE) · get_code("55955fc3f98f2a29") |
| varsize_all_gather | Ran | m3hrdadfi/rag-memory-interplay/src/atlas/dist_utils.py pointer only (licence: NONE) · get_code("fc996bc980b83cab") |
| cross_attention_forward | Not yet run | m3hrdadfi/rag-memory-interplay/src/atlas/fid.py pointer only (licence: NONE) · get_code("a94b66d049f10dc8") |
| load_or_initialize_index | Not yet run | m3hrdadfi/rag-memory-interplay/src/atlas/index_io.py pointer only (licence: NONE) · get_code("4f77c9ee1641e1ec") |
| load_passages | Not yet run | m3hrdadfi/rag-memory-interplay/src/atlas/index_io.py pointer only (licence: NONE) · get_code("af330ecdce90bbd8") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Generative language models often struggle with specialized or less-discussed knowledge. A potential solution is found in Retrieval-Augmented Generation (RAG) models which act like retrieving information before generating responses. In this study, we explore how the ATLAS approach, a RAG model, decides between what it already knows (parametric) and what it retrieves (non-parametric). We use causal mediation analysis and controlled experiments to examine how internal representations influence information processing. Our findings disentangle the effects of parametric knowledge and the retrieved context. They indicate that in cases where the model can choose between both types of information (parametric and nonparametric), it relies more on the context than the parametric knowledge. Furthermore, the analysis investigates the computations involved in how the model uses the information from the context. We find that multiple mechanisms are active within the model and can be detected with mediation analysis: first, the decision of whether the context is relevant, and second, how the encoder computes output representations to support copying when relevant. 1
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2410.05162")
get_code_for_paper("2410.05162")
have("2410.05162")
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