Github Kawaguchi Yu Tech Contribute to kawaguchi yu tech development by creating an account on github. Kimi team intelligence of foundation models tech report, 2025 paper model kimi k2 presents an open, agentic llm that achieves strong general intelligence in coding, tool use, etc. my contributions focus on improving agentic coding ability, including leading evaluation for ai scientist (paperbench) and engaging in docker scaling and scaffold.
Kawaguchi Yu Kawaguchi Yuto Github Kawaguchi yu has 6 repositories available. follow their code on github. Reload kawaguchi yu tech public notifications you must be signed in to change notification settings fork 0 star 1 code issues pull requests projects security. Latest commit history history 29 lines (29 loc) · 715 bytes master tech docker compose.yml top. {"payload":{"allshortcutsenabled":false,"filetree":{"api usecase":{"items":[{"name":"user interactor.go","path":"api usecase user interactor.go","contenttype":"file"},{"name":"user repository.go","path":"api usecase user repository.go","contenttype":"file"}],"totalcount":2},"api":{"items":[{"name":"domain","path":"api domain","contenttype":"directory"},{"name":"infra","path":"api infra","contenttype":"directory"},{"name":"interfaces","path":"api interfaces","contenttype":"directory"},{"name":"testdata","path":"api testdata","contenttype":"directory"},{"name":"usecase","path":"api usecase","contenttype":"directory"},{"name":".gitignore","path":"api .gitignore","contenttype":"file"},{"name":"dockerfile","path":"api dockerfile","contenttype":"file"},{"name":"go.mod","path":"api go.mod","contenttype":"file"},{"name":"go.sum","path":"api go.sum","contenttype":"file"},{"name":"server.go","path":"api server.go","contenttype":"file"}],"totalcount":10},"":{"items":[{"name":".github","path":".github","contenttype":"directory.
Ryuya Kawaguchi Github Latest commit history history 29 lines (29 loc) · 715 bytes master tech docker compose.yml top. {"payload":{"allshortcutsenabled":false,"filetree":{"api usecase":{"items":[{"name":"user interactor.go","path":"api usecase user interactor.go","contenttype":"file"},{"name":"user repository.go","path":"api usecase user repository.go","contenttype":"file"}],"totalcount":2},"api":{"items":[{"name":"domain","path":"api domain","contenttype":"directory"},{"name":"infra","path":"api infra","contenttype":"directory"},{"name":"interfaces","path":"api interfaces","contenttype":"directory"},{"name":"testdata","path":"api testdata","contenttype":"directory"},{"name":"usecase","path":"api usecase","contenttype":"directory"},{"name":".gitignore","path":"api .gitignore","contenttype":"file"},{"name":"dockerfile","path":"api dockerfile","contenttype":"file"},{"name":"go.mod","path":"api go.mod","contenttype":"file"},{"name":"go.sum","path":"api go.sum","contenttype":"file"},{"name":"server.go","path":"api server.go","contenttype":"file"}],"totalcount":10},"":{"items":[{"name":".github","path":".github","contenttype":"directory. Kawaguchi yu tech public notifications you must be signed in to change notification settings fork 0 star 1 code issues0 pull requests projects security insights. Ai related publications from r&d group, hitachi, ltd. this site currently contains journal and conference papers from center for technology innovation artificial intelligence. Overview this dataset consists of pairs of time series signal data and corresponding natural language texts that describe the characteristics of these time series patterns. Currently, i work closely with the tbd lab on improving the agentic coding capabilities for meta’s next gen llm. in the past years, i have also worked on a range of topics on llm post training, including code reasoning, rl, instruction following, etc.
Kawaguchi Yuki Ky Github Kawaguchi yu tech public notifications you must be signed in to change notification settings fork 0 star 1 code issues0 pull requests projects security insights. Ai related publications from r&d group, hitachi, ltd. this site currently contains journal and conference papers from center for technology innovation artificial intelligence. Overview this dataset consists of pairs of time series signal data and corresponding natural language texts that describe the characteristics of these time series patterns. Currently, i work closely with the tbd lab on improving the agentic coding capabilities for meta’s next gen llm. in the past years, i have also worked on a range of topics on llm post training, including code reasoning, rl, instruction following, etc.
Hidetoshi Kawaguchi My Hidetoshi Kawaguchi Github Overview this dataset consists of pairs of time series signal data and corresponding natural language texts that describe the characteristics of these time series patterns. Currently, i work closely with the tbd lab on improving the agentic coding capabilities for meta’s next gen llm. in the past years, i have also worked on a range of topics on llm post training, including code reasoning, rl, instruction following, etc.
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