Tootfinder

UQA: Corpus for Urdu Question Answering
Samee Arif, Sualeha Farid, Awais Athar, Agha Ali Raza
https://arxiv.org/abs/2405.01458 https://

UQA: Corpus for Urdu Question Answering
This paper introduces UQA, a novel dataset for question answering and text comprehension in Urdu, a low-resource language with over 70 million native speakers. UQA is generated by translating the Stanford Question Answering Dataset (SQuAD2.0), a large-scale English QA dataset, using a technique called EATS (Enclose to Anchor, Translate, Seek), which preserves the answer spans in the translated context paragraphs. The paper describes the process of selecting and evaluating the best translation m…

This https://arxiv.org/abs/2311.00609 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Three surprising instances of dividing
We give three counterexamples to the folklore claim that in an arbitrary theory, if a complete type $p$ over a set $B$ does not divide over $C\subseteq B$, then no extension of $p$ to a complete type over $\text{acl}(B)$ divides over $C$. Two of our examples are also the first known theories where all sets are extension bases for nonforking, but forking and dividing differ for complete types (answering a question of Adler). One example is an NSOP$_1$ theory with a complete type that forks, but …

Reservoir Sampling over Joins
Binyang Dai, Xiao Hu, Ke Yi
https://arxiv.org/abs/2404.03194 https://arxiv.org/pdf/2404.03194

Reservoir Sampling over Joins
Sampling over joins is a fundamental task in large-scale data analytics. Instead of computing the full join results, which could be massive, a uniform sample of the join results would suffice for many purposes, such as answering analytical queries or training machine learning models. In this paper, we study the problem of how to maintain a random sample over joins while the tuples are streaming in. Without the join, this problem can be solved by some simple and classical reservoir sampling algo…

Multi-hop Question Answering over Knowledge Graphs using Large Language Models
Abir Chakraborty
https://arxiv.org/abs/2404.19234 https://

Multi-hop Question Answering over Knowledge Graphs using Large Language Models
Knowledge graphs (KGs) are large datasets with specific structures representing large knowledge bases (KB) where each node represents a key entity and relations amongst them are typed edges. Natural language queries formed to extract information from a KB entail starting from specific nodes and reasoning over multiple edges of the corresponding KG to arrive at the correct set of answer nodes. Traditional approaches of question answering on KG are based on (a) semantic parsing (SP), where a logi…

This https://arxiv.org/abs/2309.05035 has been replaced.
link: https://scholar.google.com/scholar?q=a

Duplicate Question Retrieval and Confirmation Time Prediction in Software Communities
Community Question Answering (CQA) in different domains is growing at a large scale because of the availability of several platforms and huge shareable information among users. With the rapid growth of such online platforms, a massive amount of archived data makes it difficult for moderators to retrieve possible duplicates for a new question and identify and confirm existing question pairs as duplicates at the right time. This problem is even more critical in CQAs corresponding to large softwar…

This https://arxiv.org/abs/2211.15575 has been replaced.
link: https://scholar.google.com/scholar?q=a

Hyperbolicity and bounded-valued cohomology
We generalise a theorem of Gersten on surjectivity of the restriction map in $\ell^{\infty}$-cohomology of groups. This leads to applications on subgroups of hyperbolic groups, quasi-isometric distinction of finitely generated groups and $\ell^{\infty}$-cohomology calculations for some well-known classes of groups. Along the way, we obtain hyperbolicity criteria for groups of type $FP_2(\mathbb Q)$ and for those satisfying a rational homological linear isoperimetric inequality, answering a ques…

This https://arxiv.org/abs/2311.12410 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

nach0: Multimodal Natural and Chemical Languages Foundation Model
Large Language Models (LLMs) have substantially driven scientific progress in various domains, and many papers have demonstrated their ability to tackle complex problems with creative solutions. Our paper introduces a new foundation model, nach0, capable of solving various chemical and biological tasks: biomedical question answering, named entity recognition, molecular generation, molecular synthesis, attributes prediction, and others. nach0 is a multi-domain and multi-task encoder-decoder LLM …

This https://arxiv.org/abs/2402.19350 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Prompting Explicit and Implicit Knowledge for Multi-hop Question Answering Based on Human Reading Process
Pre-trained language models (PLMs) leverage chains-of-thought (CoT) to simulate human reasoning and inference processes, achieving proficient performance in multi-hop QA. However, a gap persists between PLMs' reasoning abilities and those of humans when tackling complex problems. Psychological studies suggest a vital connection between explicit information in passages and human prior knowledge during reading. Nevertheless, current research has given insufficient attention to linking input passa…

This https://arxiv.org/abs/2402.19350 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Prompting Explicit and Implicit Knowledge for Multi-hop Question Answering Based on Human Reading Process
Pre-trained language models (PLMs) leverage chains-of-thought (CoT) to simulate human reasoning and inference processes, achieving proficient performance in multi-hop QA. However, a gap persists between PLMs' reasoning abilities and those of humans when tackling complex problems. Psychological studies suggest a vital connection between explicit information in passages and human prior knowledge during reading. Nevertheless, current research has given insufficient attention to linking input passa…