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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.

9xflix com fix 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.

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Users often encounter frequent redirects and pop-up ads. Clicking these can lead to the installation of unwanted software or fileless malware, posing a threat to personal data.

A Virtual Private Network (VPN) can help you bypass geo-restrictions or ISP blocks by routing your traffic through a server in a different country.

When the main domain is down, mirror sites or "proxies" often provide the same content under a different URL. However, these carry the same security risks as the original site. 9xflix com fix

Sometimes local data can prevent a site from loading correctly. Clearing your browser’s cache and cookies can resolve minor loading glitches.

Our use of cookies * Functional cookies. * Targeting cookies. * Performance cookies. Joseph Rowntree Foundation Users often encounter frequent redirects and pop-up ads

Services like CroxyProxy allow you to unblock websites directly in your browser without needing to install separate software. Safe and Legal Alternatives

If you are struggling to access the site, these common technical "fixes" are often used by the community: When the main domain is down, mirror sites

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You may encounter a 403 Forbidden error or notice that the domain is not resolving to an IP address, which usually indicates the specific URL has been taken down or moved. How to "Fix" 9xflix Accessibility

9xflix has emerged as a popular digital platform for viewers seeking a vast library of Bollywood, Hollywood, and South Indian cinema. However, users frequently encounter accessibility issues, such as broken links, domain blocks, or intrusive advertisements.

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.