FLare (Parameter-efficient fine-tuning (LoRA family)): superseded — cited as a baseline and beaten by newer methods. 0 paper(s) critique it, 1 beat it on benchmarks — #285 of 1113 most-superseded. Sub-problem: cluster led by BLoB. Newer alternatives in the same sub-problem include iLoRA, LoRA-VBLL.

Method Drift›Parameter-efficient fine-tuning (LoRA family)

Superseded baseline#285 of 1,113 most-superseded

FLare

FLARE: Fast Learning of Animatable and Relightable Mesh Avatars

Parameter-efficient fine-tuning (LoRA family) · first seen Oct 26, 2023

superseded — cited as a baseline and beaten by newer methods

0 papers critique it · 1 beat it on benchmarks

Beaten on benchmarks

Head-to-head results where a newer method reports beating FLare. Values are copied from the source paper's tables — verify against the cited paper.

StellarF beats FLare · Accuracy [pred_len=480]
62.90 vs 48.10
StellarF: A Lora-Adapter Integrated Large Model Framework for Stellar Flare Forecasting with Historical & Statistical Data
StellarF beats FLare · Accuracy [pred_len=48]
63.60 vs 49.45
StellarF: A Lora-Adapter Integrated Large Model Framework for Stellar Flare Forecasting with Historical & Statistical Data

Newer alternatives

Recent methods in the same sub-problem, not yet superseded in the knowledge base.

iLoRA ILoRA: Federated Learning with Low-Rank Adaptation for Heterogeneous Client Aggregation
Nov 20, 2025
LoRA-VBLL Fine-tuning LLMs with variational Bayesian last layer for high-dimensional Bayesian optimization
Oct 1, 2025