Tootfinder

Some article or statement on the #Internet angers you?
Then write a reply!
But afterwards consider deleting it.
https://www.nature.com/articles/s41598-024-57916-z<…

inploid: Inploid: an online social Q&A platform
Inploid is a social question & answer website in Turkish. Users can follow others and see their questions and answers on the main page. Each user is associated with a reputability score which is influenced by feedback of others about questions and answers of the user. Each user can also specify interest in topics. The data is crawled in June 2017 and consist of 39,749 nodes and 57,276 directed links between them. In addition, for …

Bu ara Cold Case seyrediyorum, epey zamandan sonra yeniden. Müzik konusunda çok iyiydi, hala öyle...
https://open.spotify.com/track/2u2udGmop1z67EPpr91km7?si=QrJ2F_RaSO6_ANghrpQx5w

Why is everything in Kubernetes so complicated? (Don't answer that)
Somehow, I think I just enabled GPU pass-through support by running a bunch of commands I don't understand 🙂​
$ kubectl get nodes -o=jsonpath="{range .items[*]}{.metadata.name}{'\n'}{' i915: '}{.status.allocatable.gpu\.intel\.com/i915}{'\n'}"
microk8s-01
i915: 1
#kubernetes #gpu #intel

This https://arxiv.org/abs/2403.04729 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Stretchable Pneumatic Sleeve for Adaptable, Low-Displacement Anchoring in Exosuits
Despite recent advances in wearable technology, interfacing movement assistance devices with the human body remains challenging. We present a stretchable pneumatic sleeve that can anchor an exosuit actuator to the human arm with a low displacement of the actuator's mounting point relative to the body during operation. Our sleeve has the potential to serve as an adaptable attachment mechanism for exosuits, since it can adjust its pressure to only compress the arm as much as needed to transmit th…

This https://arxiv.org/abs/2403.05326 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

ChatASU: Evoking LLM's Reflexion to Truly Understand Aspect Sentiment in Dialogues
Aspect Sentiment Understanding (ASU) in interactive scenarios (e.g., Question-Answering and Dialogue) has attracted ever-more interest in recent years and achieved important progresses. However, existing studies on interactive ASU largely ignore the coreference issue for opinion targets (i.e., aspects), while this phenomenon is ubiquitous in interactive scenarios especially dialogues, limiting the ASU performance. Recently, large language models (LLMs) shows the powerful ability to integrate va…

This https://arxiv.org/abs/2305.06283 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Sub-25-dimensional counterexamples to Borsuk's conjecture in the Leech lattice?
In 1933, Karol Borsuk asked whether each bounded set in the $n$-dimensional Euclidean space can be divided into $n$+1 parts of smaller diameter. Because it would not make sense otherwise, one usually assumes that he just forgot to require that the whole set contains at least two points. The hypothesis that the answer to that question is positive became famous under the name \emph{Borsuk's conjecture}. Counterexamples are known for any $n\ge 64$, since 2013. Let $Λ$ be the (original, unscaled…

Harnessing Multi-Role Capabilities of Large Language Models for Open-Domain Question Answering
Hongda Sun, Yuxuan Liu, Chengwei Wu, Haiyu Yan, Cheng Tai, Xin Gao, Shuo Shang, Rui Yan
https://arxiv.org/abs/2403.05217

Harnessing Multi-Role Capabilities of Large Language Models for Open-Domain Question Answering
Open-domain question answering (ODQA) has emerged as a pivotal research spotlight in information systems. Existing methods follow two main paradigms to collect evidence: (1) The \textit{retrieve-then-read} paradigm retrieves pertinent documents from an external corpus; and (2) the \textit{generate-then-read} paradigm employs large language models (LLMs) to generate relevant documents. However, neither can fully address multifaceted requirements for evidence. To this end, we propose LLMQA, a gen…

Harnessing Multi-Role Capabilities of Large Language Models for Open-Domain Question Answering
Hongda Sun, Yuxuan Liu, Chengwei Wu, Haiyu Yan, Cheng Tai, Xin Gao, Shuo Shang, Rui Yan
https://arxiv.org/abs/2403.05217

Harnessing Multi-Role Capabilities of Large Language Models for Open-Domain Question Answering
Open-domain question answering (ODQA) has emerged as a pivotal research spotlight in information systems. Existing methods follow two main paradigms to collect evidence: (1) The \textit{retrieve-then-read} paradigm retrieves pertinent documents from an external corpus; and (2) the \textit{generate-then-read} paradigm employs large language models (LLMs) to generate relevant documents. However, neither can fully address multifaceted requirements for evidence. To this end, we propose LLMQA, a gen…

This https://arxiv.org/abs/2402.13709 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

SaGE: Evaluating Moral Consistency in Large Language Models
Despite recent advancements showcasing the impressive capabilities of Large Language Models (LLMs) in conversational systems, we show that even state-of-the-art LLMs are morally inconsistent in their generations, questioning their reliability (and trustworthiness in general). Prior works in LLM evaluation focus on developing ground-truth data to measure accuracy on specific tasks. However, for moral scenarios that often lack universally agreed-upon answers, consistency in model responses become…