Time-Embed BGE-M3 LMS Temporal Phase2.41
This model is a Time-Embed research checkpoint for Korean LMS temporal-expression
retrieval. It is based on BAAI/bge-m3 and was selected after Phase2.41 corrected
the collapse gate to distinguish true positive temporal alignment from negative
or global embedding saturation.
Intended Use
Use this checkpoint for Korean LMS queries where temporally equivalent expressions should be close in embedding space, for example:
일주일 전,7일 전,1주 전이번 주,이번주,금주지난 7일,최근 7일
The model is intended for retrieval/ranking experiments, not as a general-purpose replacement for every Korean embedding workload.
Source Checkpoint
Local training artifact:
research/runs/time_embed_phase2_40_boundary_context_target_compression_160_4070ti/20260626-005203
Phase2.41 did not train a new checkpoint. It reclassified the Phase2.40 checkpoint
after row-level diagnostics showed that the old aggregate near_one_rate gate was
penalizing positive-only temporal alignment.
Internal Evaluation
| suite | critical positive | negative p95 | margin p10 | negative near-one | random-pair p95 | passed |
|---|---|---|---|---|---|---|
| temporal benchmark, corrected gate | 0.712765 | 0.927091 | 0.061491 | 0.000000 | 0.525630 | true |
| focused assignment/quiz | 0.917938 | 0.935560 | 0.044867 | 0.000000 | 0.618668 | true |
| calendar benchmark | 0.873677 | 0.912210 | 0.050455 | 0.000000 | 0.624696 | true |
| semantic retention | 0.960865 | 0.934735 | 0.056170 | 0.000000 | 0.768753 | true |
Important diagnostic:
- aggregate temporal
near_one_rate: 0.067178 - positive temporal
near_one_rate: 0.135700 - negative temporal
near_one_rate: 0.000000
The high near-one mass is positive-only and corresponds to true temporal equivalence surfaces, so it is not treated as collapse.
MTEB Forgetting Check
Base model: BAAI/bge-m3
| task | metric | base | checkpoint | delta |
|---|---|---|---|---|
| KLUE-STS | main_score | 0.877152 | 0.884022 | +0.006870 |
| KorSTS | main_score | 0.802649 | 0.806705 | +0.004056 |
| KLUE-NLI | main_score | 0.700609 | 0.725655 | +0.025046 |
| SQuADKorV1Retrieval | ndcg_at_10 | 0.904150 | 0.899820 | -0.004330 |
| SQuADKorV1Retrieval | mrr_at_10 | 0.880194 | 0.875764 | -0.004430 |
No general catastrophic forgetting was detected under the project thresholds.
Loading
from FlagEmbedding import BGEM3FlagModel
model = BGEM3FlagModel(
"kev-KOH/time-embed-bge-m3-lms-temporal-phase2-41",
use_fp16=True,
)
embeddings = model.encode(
["일주일 전 업로드된 데이터 자료 찾아줘", "7일 전 업로드된 데이터 자료 찾아줘"],
return_dense=True,
return_sparse=False,
return_colbert_vecs=False,
)["dense_vecs"]
Provenance
Project repository: Han-taz/Time-Embed
Relevant local documentation:
wiki/2026-06-26/research/phase2-41-collapse-gate-correction-design.mdwiki/2026-06-26/eval-results/phase2-41-collapse-gate-corrected-phase2-40/metrics-summary.mdwiki/2026-06-26/eval-results/phase2-41-collapse-gate-corrected-phase2-40/mteb-forgetting/README.md