Molly Jane Collection 2021 Jun 2026

Are LLMs following the correct reasoning paths?

Bangzheng Li, Ben Zhou, Fei Wang, Xingyu Fu, Dan Roth, Muhao Chen,

▶ University of California, Davis ▶ University of Pennsylvania   ▶ University of Southern California
arXiv Code Dataset

We propose a novel probing method and benchmark called EUREQA. EUREQA is an entity-searching task where a model finds a missing entity based on described multi-hop relations with other entities. These deliberately designed multi-hop relations create deceptive semantic associations, and models must stick to the correct reasoning path instead of incorrect shortcuts to find the correct answer. Experiments show that existing LLMs cannot follow correct reasoning paths and resist the attempt of greedy shortcuts. Analyses provide further evidence that LLMs rely on semantic biases to solve the task instead of proper reasoning, questioning the validity and generalizability of current LLMs’ high performances.

molly jane collection
LLMs make errors when correct surface-level semantic cues-entities are recursively replaced with descriptions, and the errors are likely related to token similarity. GPT-3.5-turbo is used for this example.

molly jane collection The EUREQA dataset

Download the dataset from [Dataset]

In EUREQA, every question is constructed through an implicit reasoning chain. The chain is constructed by parsing DBPedia. Each layer comprises three components: an entity, a fact about the entity, and a relation between the entity and its counterpart from the next layer. The layers stack up to create chains with different depths of reasoning. We verbalize reasoning chains into natural sentences and anonymize the entity of each layer to create the question. Questions can be solved layer by layer and each layer is guaranteed a unique answer. EUREQA is not a knowledge game: we adopt a knowledge filtering process that ensures that most LLMs have sufficient world knowledge to answer our questions.
EUREQA comprises a total of 2,991 questions of different reasoning depths and difficulties. The entities encompass a broad spectrum of topics, effectively reducing any potential bias arising from specific entity categories. These data are great for analyzing the reasoning processes of LLMs

Image 1
Categories of entities in EUREQA
Image 2
Splits of questions in EUREQA.

molly jane collection Performance

Here we present the accuracy of ChatGPT, Gemini-Pro and GPT-4 on the hard set of EUREQA across different depths d of reasoning (number of layers in the questions). We evaluate two prompt strategies: direct zero-shot prompt and ICL with two examples. In general, with the entities recursively substituted by the descriptions of reasoning chaining layers, and therefore eliminating surface-level semantic cues, these models generate more incorrect answers. When the reasoning depth increases from one to five on hard questions, there is a notable decline in performance for all models. This finding underscores the significant impact that semantic shortcuts have on the accuracy of responses, and it also indicates that GPT-4 is considerably more capable of identifying and taking advantage of these shortcuts.

depth d=1 d=2 d=3 d=4 d=5
direct icl direct icl direct icl direct icl direct icl
ChatGPT 22.3 53.3 7.0 40.0 5.0 39.2 3.7 39.3 7.2 39.0
Gemini-Pro 45.0 49.3 29.5 23.5 27.3 28.6 25.7 24.3 17.2 21.5
GPT-4 60.3 76.0 50.0 63.7 51.3 61.7 52.7 63.7 46.9 61.9

Molly Jane Collection 2021 Jun 2026

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The Molly Jane Collection sits in the "contemporary" price bracket. You aren't paying fast-fashion prices, but you aren't paying luxury designer prices either.

The Molly Jane Collection is a fashion brand that is quickly gaining a loyal following among fashionistas of all ages. With its focus on high-quality materials, attention to detail, and affordable prices, it's no wonder that this brand is becoming a go-to destination for women who want to stay stylish and on-trend without sacrificing their personal style. Whether you're looking for a statement-making dress or a simple, everyday top, the Molly Jane Collection has something for everyone. So why not check out the brand's website and social media channels to see what all the fuss is about? One of the most prominent fashion-forward brands associated

The collection favors soft lighting, blue and green color palettes, and cozy textures. Popular Items:

Here is a full review of the Molly Jane Collection, breaking down the aesthetics, quality, fit, and overall value. While she stepped down to focus on personal

The Molly Jane Collection was founded by Molly Jane, a talented fashion designer with a vision to create clothing that is both stylish and accessible. With a background in fashion design and a passion for creating clothing that makes women feel confident and beautiful, Molly Jane set out to build a brand that would offer high-quality, on-trend pieces at affordable prices. Since its inception, the brand has grown rapidly, with a loyal customer base and a strong online presence.

Acknowledgement

This website is adapted from Nerfies, UniversalNER and LLaVA, licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. We thank the LLaMA team for giving us access to their models.

Usage and License Notices: The data abd code is intended and licensed for research use only. They are also restricted to uses that follow the license agreement of LLaMA, ChatGPT, and the original dataset used in the benchmark. The dataset is CC BY NC 4.0 (allowing only non-commercial use) and models trained using the dataset should not be used outside of research purposes.