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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.

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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.

www tamelsex exclusive 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.

www tamelsex exclusive 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

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For decades, the "rake" or the "playboy" reigned supreme in romance fiction—the idea that a prolific dater could be tamed by the right person. While this remains a popular fantasy, there has been a noticeable cultural shift toward the "green flag" partner.

Modern audiences are increasingly rejecting the "toxicity" of love triangles in favor of stories where boundaries are respected and communication is prioritized. The rise of the "touch her and you die" trope (in a protective, non-possessive context) and the "obsessed love interest" speaks to a desire for intensity without ambiguity.

We are seeing a redefinition of what makes a story "spicy." It isn't the variety of partners, but the depth of the connection with one. The most romantic moments in recent media history aren't about grand gestures to win someone over; they are about the quiet, consistent choice to stay. www tamelsex exclusive

In the landscape of modern storytelling, few tropes generate as much visceral reaction as the "love triangle." Scroll through any book community on social media, and you will find heated debates: Team Peeta vs. Team Gale, Team Edward vs. Team Jacob. Yet, despite the drama that competing suitors provide, there is a profound, quiet comfort found in the counter-trope: the exclusive relationship.

The exclusive romance—where two characters commit solely to one another, often early in the narrative—is frequently dismissed by critics as "vanilla" or lacking in conflict. However, a closer look reveals that these storylines offer a sophisticated exploration of trust, vulnerability, and the heavy lifting required to build a shared life. In a culture often obsessed with the thrill of the chase, exclusive relationships in fiction remind us that the real adventure begins after the commitment is made. For decades, the "rake" or the "playboy" reigned

Why do readers and viewers flock to stories of exclusive devotion? The answer may lie in "attachment theory." In psychology, a secure attachment is formed when a partner is consistent and reliable. In fiction, exclusive relationships provide a narrative "safe harbor."

In an era of dating apps, "ghosting," and situationships, real-world romance can feel precarious. Consuming media where characters are explicitly exclusive provides a form of escapism that isn't about fantasy, but about security. It satisfies a deep-seated craving for a world where a person’s word is their bond, and where love is not a competition to be won, but a pact to be honored. The rise of the "touch her and you

This is perhaps why the "emotional intimacy" trope has surged in popularity. Readers are finding more heat in a scene where a character says, "I’m yours, and I’m not looking anywhere else," than in a chaotic love triangle where the protagonist is perpetually torn.

This is the sweet spot of contemporary romance writing. The characters are faithful to each other, but the emotional timeline is mismatched. Think To All the Boys I’ve Loved Before: Lara Jean and Peter are "fake dating" into exclusivity, but the real love lags behind the contract. Watching them catch up is the plot.

Once exclusivity is achieved, show the mundane morning after. The snoring. The mismatched coffee orders. Real romance is not just passion; it is choosing the same person during a fight about dirty dishes. The best storylines (like The Marvelous Mrs. Maisel’s Joel and Midge) fail because they skip this part.

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.