Tootfinder

dblp_cite: DBLP citations (2014)
Citations among papers contained in the DBLP computer science bibliography. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. This snapshot from May 2014.
This network has 12590 nodes and 49759 edges.
Tags: Informational, Citation, Unweighted

Hierarchical Bracketing Encodings Work for Dependency Graphs
Ana Ezquerro, Carlos G\'omez-Rodr\'iguez, David Vilares
https://arxiv.org/abs/2509.09388 https://

Hierarchical Bracketing Encodings Work for Dependency Graphs
We revisit hierarchical bracketing encodings from a practical perspective in the context of dependency graph parsing. The approach encodes graphs as sequences, enabling linear-time parsing with $n$ tagging actions, and still representing reentrancies, cycles, and empty nodes. Compared to existing graph linearizations, this representation substantially reduces the label space while preserving structural information. We evaluate it on a multilingual and multi-formalism benchmark, showing competit…

internet_top_pop: Internet topology (PoP level) (1969-2012)
Assorted snapshots of internet graph at the Point of Presence (PoP) level (which lies between the IP and AS levels), collected from around the world and at various times. The earliest snapshots are for ARPANET (1969-1972), with a few more from pre-2000. Most are from 2006 onward. Metadata include link type or speed, longitudes, and latitudes of nodes, URL, and date of record.
This network has 38 nodes and 39 edges.

Few-shot Personalization via In-Context Learning for Speech Emotion Recognition based on Speech-Language Model
Mana Ihori, Taiga Yamane, Naotaka Kawata, Naoki Makishima, Tomohiro Tanaka, Satoshi Suzuki, Shota Orihashi, Ryo Masumura
https://arxiv.org/abs/2509.08344

Few-shot Personalization via In-Context Learning for Speech Emotion Recognition based on Speech-Language Model
This paper proposes a personalization method for speech emotion recognition (SER) through in-context learning (ICL). Since the expression of emotions varies from person to person, speaker-specific adaptation is crucial for improving the SER performance. Conventional SER methods have been personalized using emotional utterances of a target speaker, but it is often difficult to prepare utterances corresponding to all emotion labels in advance. Our idea to overcome this difficulty is to obtain spe…

product_space: Atlas of Economic Complexity export network
Two networks of economic products, where a pair of products are connected if they are exported at similar rates by the same countries. The data are a projection from a bipartite network of nations and the products they export. Edges weights represent a similarity score (called "proximity"). Data based on UN Comtrade worldwide trade patterns. SITC network based on the Standard International Trade Classification and HS …

product_space: Atlas of Economic Complexity export network
Two networks of economic products, where a pair of products are connected if they are exported at similar rates by the same countries. The data are a projection from a bipartite network of nations and the products they export. Edges weights represent a similarity score (called "proximity"). Data based on UN Comtrade worldwide trade patterns. SITC network based on the Standard International Trade Classification and HS …

faculty_hiring: Faculty hiring networks (Comp. Sci., Business, History)
Three networks of faculty hiring in Computer Science Departments, Business Schools, and History Departments. Each node is a PhD-granting institution in the respective field, and a directed edge (i,j) indicates that a person received their PhD from node i and was tenure-track faculty at node j during time of collection (2011-2013). All data collected from faculty public rosters at the sampled institutions.
Thi…

faculty_hiring_us: Faculty hiring networks in the US (2022)
Networks of faculty hiring for all PhD-granting US universities over the decade 2011–2020. Each node is a PhD-granting institution, and a directed edge (i,j) indicates that a person received their PhD from node i and was tenure-track faculty at node j during time of collection (2011-2020). This dataset is divided into separate networks for all 107 fields, as well as aggregate networks for 8 domains, and an overall network for …

faculty_hiring: Faculty hiring networks (Comp. Sci., Business, History)
Three networks of faculty hiring in Computer Science Departments, Business Schools, and History Departments. Each node is a PhD-granting institution in the respective field, and a directed edge (i,j) indicates that a person received their PhD from node i and was tenure-track faculty at node j during time of collection (2011-2013). All data collected from faculty public rosters at the sampled institutions.
Thi…