Papers › Episodic Memories Generation and Evaluation Benchmark for Large Language Models

Episodic Memories Generation and Evaluation Benchmark for Large Language Models

21 Jan 2025arXiv:2501.13121archive 2025-07-28

Alexis Huet, Zied Ben Houidi, Dario Rossi

Episodic memory -- the ability to recall specific events grounded in time and space -- is a cornerstone of human cognition, enabling not only coherent storytelling, but also planning and decision-making. Despite their remarkable capabilities, Large Language Models (LLMs) lack a robust mechanism for episodic memory: we argue that integrating episodic memory capabilities into LLM is essential for advancing AI towards human-like cognition, increasing their potential to reason consistently and ground their output in real-world episodic events, hence avoiding confabulations. To address this challenge, we introduce a comprehensive framework to model and evaluate LLM episodic memory capabilities. Drawing inspiration from cognitive science, we develop a structured approach to represent episodic events, encapsulating temporal and spatial contexts, involved entities, and detailed descriptions. We synthesize a unique episodic memory benchmark, free from contamination, and release open source code and datasets to assess LLM performance across various recall and episodic reasoning tasks. Our evaluation of state-of-the-art models, including GPT-4 and Claude variants, Llama 3.1, and o1-mini, reveals that even the most advanced LLMs struggle with episodic memory tasks, particularly when dealing with multiple related events or complex spatio-temporal relationships -- even in contexts as short as 10k-100k tokens.

PaperPDFCodeCode Syntology ran

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

For agents, Syntology's MCP tool lists every function and class Syntology harvested from this paper and whether it ran (how to connect): get_harvested_code_for_paper(arxiv_id="2501.13121")

Code

Syntology Ran 0 of 14 code samples harvested from 1 repository linked to this paper; 14 have no recorded run.

By repository: official repository: 14 samples from 1 repository, 0 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

ahstat/episodic-memory-benchmark officialmentioned in papermentioned on GitHubMIT report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

14 samples harvested; 0 ran; 0 honoured the contract we drafted; 14 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.

14unverified

Licence: 14 of the 14 samples are pointer only, meaning Syntology does not serve that copy's text. This page shows no code text for any sample; each one links to its file in the repository.

Harvested from ahstat/episodic-memory-benchmark. “Ran” means the sample executed on a synthesized input. It does not mean the output is correct, and nothing here reproduces the paper's results. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code.

Each sample ends with its code_sha256, Syntology's identity for that exact code. An agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

Repository labels, per sample. official repository: The archive marks this repository official for the paper. named in the paper: The archive records that the paper mentions this repository; it is not marked official. community (archive-listed): In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper. found in paper text by Syntology: Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted. community: Not in the archive's code links for this paper; a community repository Syntology harvested. Samples from a repository marked official are listed first. Licence labels name the repository's licence as recorded at harvest. “Pointer only” means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence label for the reason. File links open the file on GitHub at the default branch, which may have changed since the harvest.

append_number_if_duplicate ahstat/episodic-memory-benchmark/epbench/src/evaluation/scoring_answers.py official repository unverified MIT recorded; this copy not marked cleared · pointer only · f7b7adaede9c1cc0 · report
check_and_remove ahstat/episodic-memory-benchmark/epbench/src/evaluation/generator_answers_1_prompting.py official repository unverified MIT recorded; this copy not marked cleared · pointer only · 24de7d7bf124988c · report
convert_uncertainty_format ahstat/episodic-memory-benchmark/epbench/src/evaluation/ranking.py official repository unverified MIT recorded; this copy not marked cleared · pointer only · b57fd480e6da09ab · report
f1_score_func ahstat/episodic-memory-benchmark/epbench/src/evaluation/scoring_answers.py official repository unverified MIT recorded; this copy not marked cleared · pointer only · de963d0285a5664a · report
generate_episodic_memory_prompt ahstat/episodic-memory-benchmark/epbench/src/evaluation/prompts.py official repository unverified MIT recorded; this copy not marked cleared · pointer only · 9418d2d478ea0305 · report
generate_episodic_memory_rag_prompt ahstat/episodic-memory-benchmark/epbench/src/evaluation/generator_answers_2_rag.py official repository unverified MIT recorded; this copy not marked cleared · pointer only · 15280c4c08144e4a · report
get_short_name ahstat/episodic-memory-benchmark/epbench/src/evaluation/ranking.py official repository unverified MIT recorded; this copy not marked cleared · pointer only · b0421b36bcc3addb · report
get_short_name_from_model_name ahstat/episodic-memory-benchmark/epbench/src/evaluation/ranking.py official repository unverified MIT recorded; this copy not marked cleared · pointer only · 76180a167954eebf · report
iteration_verbose_func ahstat/episodic-memory-benchmark/epbench/src/generation/generate_2_paragraph.py official repository unverified MIT recorded; this copy not marked cleared · pointer only · 58fd52aa3c394c45 · report
judge_prompt_func ahstat/episodic-memory-benchmark/epbench/src/evaluation/scoring_answers.py official repository unverified MIT recorded; this copy not marked cleared · pointer only · 5822f5812826c314 · report
patch_for_ensuring_token_size_lower_130k_in_llama3 ahstat/episodic-memory-benchmark/epbench/src/evaluation/generator_answers_1_prompting.py official repository unverified MIT recorded; this copy not marked cleared · pointer only · 415511e9a094dd88 · report
retrieve_fileid ahstat/episodic-memory-benchmark/epbench/src/evaluation/generator_answers_3_ftuning.py official repository unverified MIT recorded; this copy not marked cleared · pointer only · 8a70f9eda3e9c541 · report
upload_ftuning_input ahstat/episodic-memory-benchmark/epbench/src/evaluation/generator_answers_3_ftuning.py official repository unverified MIT recorded; this copy not marked cleared · pointer only · 56554feb5a10d6e4 · report
whether_do_this_q ahstat/episodic-memory-benchmark/epbench/src/evaluation/generator_answers_1_prompting.py official repository unverified MIT recorded; this copy not marked cleared · pointer only · 7bb43402032a22a1 · report

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Methods

Absolute Position EncodingsAdamAttentionBPEDense ConnectionsDropoutGPT-4LLaMALabel SmoothingLayer NormalizationLinear LayerMulti-Head AttentionPosition-Wise Feed-Forward LayerResidual ConnectionSoftmaxTransformer

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections