Fetching the paper…
Reading the bibliography…
This paper introduces a framework that leverages Large Language Models (LLMs) to answer natural language queries about General Transit Feed Specification (GTFS) data.
An information-theoretic perspective of tf–idf measures
Aizawa, A., 2003 · 2003
Earlier work this paper cites.
Language Models are Few-Shot Learners
Brown, T.B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D.M., Wu, J., Winter, C., Hesse, C., Chen, M., Sigler, E., Litwin, M., Gray, S., Chess, B., Clark, J., Berner, C., McCandlish, S., Radford, A., Sutskever, I., Amodei, D., 2020 · 2005
Earlier work this paper cites.
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W.t., Rocktäschel, T., Riedel, S., Kiela, D., 2021 · 2005
Earlier work this paper cites.
Measuring Massive Multitask Language Understanding
Hendrycks, D., Burns, C., Basart, S., Zou, A., Mazeika, M., Song, D., Steinhardt, J., 2021 · 2009
Earlier work this paper cites.
How Google and Portland’s TriMet Set the Standard for Open Transit Data - Streetsblog San Francisco
Roth, M., 2010 · 2010
Earlier work this paper cites.
Pioneering Open Data Standards: The GTFS Story, in: Beyond Transparency: Open Data and the Future of Civic Innovation. Code for America Press San Francisco, pp. 125–135
McHugh, B., 2013 · 2013
Earlier work this paper cites.
Innovative GTFS Data Application for Transit Network Analysis Using a Graph-Oriented Method
Fortin, P., Morency, C., Trépanier, M., 2016 · 2016
Earlier work this paper cites.
An efficient General Transit Feed Specification (GTFS) enabled algorithm for dynamic transit accessibility analysis
Fayyaz, K., Liu, X.C., Zhang, G., 2017 · 2017
Earlier work this paper cites.
GTFS-Viz: Tool for preprocessing and visualizing GTFS data, in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers, ACM, Maui Hawaii. pp. 388–396
Kunama, N., Worapan, M., Phithakkitnukoon, S., Demissie, M., 2017 · 2017
Earlier work this paper cites.
Assessing public transit performance using real-time data: Spatiotemporal patterns of bus operation delays in Columbus, Ohio, USA
Park, Y., Mount, J., Liu, L., Xiao, N., Miller, H.J., 2020 · 2019
Earlier work this paper cites.
Spatio-Temporal Analysis Of Public Transportation System Using Static Transit Accessibility Methodological Framework
Prajapati, A., Bhattrai, N., Bajracharya, T., 2020 · 2020
Earlier work this paper cites.
Training Verifiers to Solve Math Word Problems
Cobbe, K., Kosaraju, V., Bavarian, M., Chen, M., Jun, H., Kaiser, L., Plappert, M., Tworek, J., Hilton, J., Nakano, R., Hesse, C., Schulman, J., 2021 · 2021
Earlier work this paper cites.
R5r: Rapid Realistic Routing on Multimodal Transport Networks with R 5 in R
Pereira, R.H.M., Saraiva, M., Herszenhut, D., Braga, C.K.V., Conway, M.W., 2021 · 2021
Earlier work this paper cites.
A spatiotemporal analysis of transit accessibility to low-wage jobs in Miami-Dade County
Yan, X., Bejleri, I., Zhai, L., 2022 · 2021
Earlier work this paper cites.
CERT: Continual Pre-Training on Sketches for Library-Oriented Code Generation
Zan, D., Chen, B., Yang, D., Lin, Z., Kim, M., Guan, B., Wang, Y., Chen, W., Lou, J.G., 2022 · 2022
Earlier work this paper cites.
Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods
Crothers, E., Japkowicz, N., Viktor, H., 2023 · 2023
Cited alongside, same era.
Receive, Reason, and React: Drive as You Say with Large Language Models in Autonomous Vehicles
Cui, C., Ma, Y., Cao, X., Ye, W., Wang, Z., 2023 · 2023
Cited alongside, same era.
LLM Powered Sim-to-real Transfer for Traffic Signal Control
Da, L., Gao, M., Mei, H., Wei, H., 2023 · 2023
Cited alongside, same era.
Drive Like a Human: Rethinking Autonomous Driving with Large Language Models
Fu, D., Li, X., Wen, L., Dou, M., Cai, P., Shi, B., Qiao, Y., 2023 · 2023
Cited alongside, same era.
Model Card Addendum: Claude 3.5 Haiku and Upgraded Claude 3.5 Sonnet
Anthropic, 2024 · 2024
Closest in time.
Text2SQL is Not Enough: Unifying AI and Databases with TAG
Biswal, A., Patel, L., Jha, S., Kamsetty, A., Liu, S., Gonzalez, J.E., Guestrin, C., Zaharia, M., 2024 · 2024
Closest in time.
Bus stop spacing statistics: Theory and evidence
Devunuri, S., Lehe, L.J., Qiam, S., Pandey, A., Monzer, D., 2024a · 2024
Closest in time.
Prompting Is All You Need: Automated Android Bug Replay with Large Language Models
Feng, S., Chen, C., 2024 · 2024
Closest in time.
Retrieval-Augmented Generation for Large Language Models: A Survey
Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., Wang, M., Wang, H., 2024 · 2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Haluptzok, P., Bowers, M., Kalai, A.T., 2023 · 2023
Cited alongside, same era.
From Words to Code: Harnessing Data for Program Synthesis from Natural Language
Khatry, A., Cahoon, J., Henkel, J., Deep, S., Emani, V., Floratou, A., Gulwani, S., Le, V., Raza, M., Shi, S., Singh, M., Tiwari, A., 2023 · 2023
Cited alongside, same era.
Lost in the Middle: How Language Models Use Long Contexts
Liu, N.F., Lin, K., Hewitt, J., Paranjape, A., Bevilacqua, M., Petroni, F., Liang, P., 2023 · 2023
Cited alongside, same era.
Large Language Models in Analyzing Crash Narratives – A Comparative Study of ChatGPT, BARD and GPT-4
Mumtarin, M., Chowdhury, M.S., Wood, J., 2023 · 2023
Cited alongside, same era.
Exploring the time geography of public transport networks with the gtfs2gps package
Pereira, R.H.M., Andrade, P.R., Vieira, J.P.B., 2023 · 2023
Cited alongside, same era.
In-Context Impersonation Reveals Large Language Models’ Strengths and Biases
Salewski, L., Alaniz, S., Rio-Torto, I., Schulz, E., Akata, Z., 2023 · 2023
Cited alongside, same era.
Toolformer: Language Models Can Teach Themselves to Use Tools
Schick, T., Dwivedi-Yu, J., Dessì, R., Raileanu, R., Lomeli, M., Zettlemoyer, L., Cancedda, N., Scialom, T., 2023 · 2023
Cited alongside, same era.
ExpertPrompting: Instructing Large Language Models to be Distinguished Experts
Xu, B., Yang, A., Lin, J., Wang, Q., Zhou, C., Zhang, Y., Mao, Z., 2023 · 2023
Cited alongside, same era.
RULER: What’s the Real Context Size of Your Long-Context Language Models?
Hsieh, C.P., Sun, S., Kriman, S., Acharya, S., Rekesh, D., Jia, F., Zhang, Y., Ginsburg, B., 2024 · 2024
Closest in time.
GTFS2STN: Analyzing GTFS Transit Data by Generating Spatiotemporal Transit Network
Liu, D., Guo, J., Gu, Y., King, M., Han, L.D., Brakewood, C., 2024 · 2024
Closest in time.
The Crossroads of LLM and Traffic Control: A Study on Large Language Models in Adaptive Traffic Signal Control
Movahedi, M., Choi, J., 2024 · 2024
Closest in time.
Towards a Method for Evaluating Bus Stop Infrastructure with Street Level Images and Large Language Models
Oliveira, A., Espadoto, M., Hirata Jr, R., Damaceno, R., Cesar, R., 2024 · 2024
Closest in time.
OpenAI, Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F.L., Almeida, D., Altenschmidt, J., Altman, S., Anadkat, S., Avila, R., Babuschkin, I., Balaji, S., Balcom, V., Baltescu, P., Bao, H., Bavarian, M., Belgum, J., Bello, I., Berdine, J., Bernadett-Shapiro, G., Berner, C., Bogdonoff, L., Boiko, O., Boyd, M., Brakman, A.L., Brockman, G., Brooks, T., Brundage, M., Button, K., Cai, T., Campbell, R., Cann, A., Carey, B., Carlson, C., Carmichael, R., Chan, B., Chang, C., Chantzis, F., Chen, D., Chen, S., Chen, R., Chen, J., Chen, M., Chess, B., Cho, C., Chu, C., Chung, H.W., Cummings, D., Currier, J., Dai, Y., Decareaux, C., Degry, T., Deutsch, N., Deville, D., Dhar, A., Dohan, D., Dowling, S., Dunning, S., Ecoffet, A., Eleti, A., Eloundou, T., Farhi, D., Fedus, L., Felix, N., Fishman, S.P., Forte, J., Fulford, I., Gao, L., Georges, E., Gibson, C., Goel, V., Gogineni, T., Goh, G., Gontijo-Lopes, R., Gordon, J., Grafstein, M., Gray, S., Greene, R., Gross, J., Gu, S.S., Guo, Y., Hallacy, C., Han, J., Harris, J., He, Y., Heaton, M., Heidecke, J., Hesse, C., Hickey, A., Hickey, W., Hoeschele, P., Houghton, B., Hsu, K., Hu, S., Hu, X., Huizinga, J., Jain, S., Jain, S., Jang, J., Jiang, A., Jiang, R., Jin, H., Jin, D., Jomoto, S., Jonn, B., Jun, H., Kaftan, T., Kaiser, Ł., Kamali, A., Kanitscheider, I., Keskar, N.S., Khan, T., Kilpatrick, L., Kim, J.W., Kim, C., Kim, Y., Kirchner, J.H., Kiros, J., Knight, M., Kokotajlo, D., Kondraciuk, Ł., Kondrich, A., Konstantinidis, A., Kosic, K., Krueger, G., Kuo, V., Lampe, M., Lan, I., Lee, T., Leike, J., Leung, J., Levy, D., Li, C.M., Lim, R., Lin, M., Lin, S., Litwin, M., Lopez, T., Lowe, R., Lue, P., Makanju, A., Malfacini, K., Manning, S., Markov, T., Markovski, Y., Martin, B., Mayer, K., Mayne, A., McGrew, B., McKinney, S.M., McLeavey, C., McMillan, P., McNeil, J., Medina, D., Mehta, A., Menick, J., Metz, L., Mishchenko, A., Mishkin, P., Monaco, V., Morikawa, E., Mossing, D., Mu, T., Murati, M., Murk, O., Mély, D., Nair, A., Nakano, R., Nayak, R., Neelakantan, A., Ngo, R., Noh, H., Ouyang, L., O’Keefe, C., Pachocki, J., Paino, A., Palermo, J., Pantuliano, A., Parascandolo, G., Parish, J., Parparita, E., Passos, A., Pavlov, M., Peng, A., Perelman, A., Peres, F.d.A.B., Petrov, M., Pinto, H.P.d.O., Michael, Pokorny, Pokrass, M., Pong, V.H., Powell, T., Power, A., Power, B., Proehl, E., Puri, R., Radford, A., Rae, J., Ramesh, A., Raymond, C., Real, F., Rimbach, K., Ross, C., Rotsted, B., Roussez, H., Ryder, N., Saltarelli, M., Sanders, T., Santurkar, S., Sastry, G., Schmidt, H., Schnurr, D., Schulman, J., Selsam, D., Sheppard, K., Sherbakov, T., Shieh, J., Shoker, S., Shyam, P., Sidor, S., Sigler, E., Simens, M., Sitkin, J., Slama, K., Sohl, I., Sokolowsky, B., Song, Y., Staudacher, N., Such, F.P., Summers, N., Sutskever, I., Tang, J., Tezak, N., Thompson, M.B., Tillet, P., Tootoonchian, A., Tseng, E., Tuggle, P., Turley, N., Tworek, J., Uribe, J.F.C., Vallone, A., Vijayvergiya, A., Voss, C., Wainwright, C., Wang, J.J., Wang, A., Wang, B., Ward, J., Wei, J., Weinmann, C.J., Welihinda, A., Welinder, P., Weng, J., Weng, L., Wiethoff, M., Willner, D., Winter, C., Wolrich, S., Wong, H., Workman, L., Wu, S., Wu, J., Wu, M., Xiao, K., Xu, T., Yoo, S., Yu, K., Yuan, Q., Zaremba, W., Zellers, R., Zhang, C., Zhang, M., Zhao, S., Zheng, T., Zhuang, J., Zhuk, W., Zoph, B., 2024 · 2024
Closest in time.
G2Viz: An online tool for visualizing and analyzing a public transit system from GTFS data
Para, S., Wirotsasithon, T., Jundee, T., Demissie, M.G., Sekimoto, Y., Biljecki, F., Phithakkitnukoon, S., 2024 · 2024
Closest in time.
Evaluating In-Context Learning of Libraries for Code Generation
Patel, A., Reddy, S., Bahdanau, D., Dasigi, P., 2024 · 2024
Closest in time.
Syed, U., Light, E., Guo, X., Zhang, H., Qin, L., Ouyang, Y., Hu, B., 2024 · 2024
Closest in time.
Wang, J., Shalaby, A., 2024 · 2024
Closest in time.
TrafficGPT: Viewing, processing and interacting with traffic foundation models
Zhang, S., Fu, D., Liang, W., Zhang, Z., Yu, B., Cai, P., Yao, B., 2024d · 2024
Closest in time.