Fiedel, Noah
Dima
16 papers on CoChat
Most cited papers
- Verified
PaLM: Scaling Language Modeling with Pathways
Chowdhery, A., Narang, S., Devlin, J., Bosma, M., Mishra, G., Roberts, A., Barham, P., Chung, H. W., Sutton, C., Gehrmann, S., et al. (2022) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 2,590
- Verified
Gemma 3 Technical Report
Gemma Team, Kamath, A., Ferret, J., Pathak, S., Vieillard, N., Merhej, R., Perrin, S., Matejovicova, T., Ramé, A., Rivière, M., et al. (2025) · arXiv
Multimodal Machine Learning ApplicationsTopic Modeling
Cited by 1,156
- Verified
Towards a Human-like Open-Domain Chatbot
Adiwardana, D., Luong, M.-T., So, D. R., Hall, J., Fiedel, N., Thoppilan, R., Yang, Z., Kulshreshtha, A., Nemade, G., Lu, Y., et al. (2020) · arXiv
Speech and dialogue systemsTopic Modeling
Cited by 614
- Verified
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 569
- Verified
TFX: A TensorFlow-Based Production-Scale Machine Learning Platform
Baylor, D., Breck, E., Cheng, H.-T., Fiedel, N., Foo, C. Y., Haque, Z., Haykal, S., Ispir, M., Jain, V., Koc, L., et al. (2017) · Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Software Engineering Techniques and PracticesScientific Computing and Data Management
Cited by 350
- Verified
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini Team, Georgiev, P., Lei, V. I., Burnell, R., Bai, L., Gulati, A., Tanzer, G., Vincent, D., Pan, Z., Wang, S., et al. (2024) · arXiv
Multimodal Machine Learning ApplicationsTopic Modeling
Cited by 306
- Verified
Gemma: Open Models Based on Gemini Research and Technology
Gemma Team, Mesnard, T., Hardin, C., Dadashi, R., Bhupatiraju, S., Pathak, S., Sifre, L., Rivière, M., Kale, M. S., Love, J., et al. (2024) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 284
- Verified
Levels of AGI for Operationalizing Progress on the Path to AGI
Morris, M. R., Sohl-Dickstein, J., Fiedel, N., Warkentin, T., Dafoe, A., Faust, A., Farabet, C., & Legg, S. (2023) · arXiv
Psychiatry, Mental Health, NeuroscienceArtificial Intelligence Applications
Cited by 274
- Verified
TensorFlow-Serving: Flexible, High-Performance ML Serving
Olston, C., Fiedel, N., Gorovoy, K., Harmsen, J., Lao, L., Li, F., Rajashekhar, V., Ramesh, S., & Soyke, J. (2017) · arXiv
Cloud Computing and Resource ManagementAdvanced Neural Network Applications
Cited by 171
- Verified
Gemma 2: Improving Open Language Models at a Practical Size
Gemma Team, Riviere, M., Pathak, S., Sessa, P. G., Hardin, C., Bhupatiraju, S., Hussenot, L., Mesnard, T., Shahriari, B., Ramé, A., et al. (2024) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 149
- Verified
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv
Multimodal Machine Learning ApplicationsTopic Modeling
Cited by 69
- Verified
TALM: Tool Augmented Language Models
Parisi, A., Zhao, Y., & Fiedel, N. (2022) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 35
- Verified
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models
Singh, A., Co-Reyes, J. D., Agarwal, R., Anand, A., Patil, P., Garcia, X., Liu, P. J., Harrison, J., Lee, J., Xu, K., et al. (2023) · arXiv
Topic ModelingDomain Adaptation and Few-Shot Learning
Cited by 10
- Verified
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models
Botev, A., De, S., Smith, S. L., Fernando, A., Muraru, G.-C., Haroun, R., Berrada, L., Pascanu, R., Sessa, P. G., Dadashi, R., et al. (2024) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 5
- Verified
Because we have LLMs, we Can and Should Pursue Agentic Interpretability
Kim, B., Hewitt, J., Nanda, N., Fiedel, N., & Tafjord, O. (2025) · arXiv
Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI
Cited by 1
- Verified
Enhancing LLM Planning Capabilities through Intrinsic Self-Critique
Bohnet, B., Kamienny, P.-A., Sedghi, H., Gorur, D., Awasthi, P., Parisi, A., Swersky, K., Liu, R., Nova, A., & Fiedel, N. (2025) · arXiv
AI-based Problem Solving and PlanningArtificial Intelligence in Games
Cited by 0
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