1/ RL for improving task success has made LLMs remarkably capable. But what happens when the model fails? Turns out, training for graceful failure can be surprisingly tricky!
Very excited to share our new paper: Training Language Models to Fail Gracefully
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What to do when you have zero rewards during RL?
We benchmarked RL baselines on a simple star-graph task where they underperform in zero reward scenarios.
Turns out, a dead simple data-centric intervention of just adding easy samples of the task helps unlock RL training! 👇
Nice to see our work (CORE) on using LLMs to resolve code quality issues flagged by static analysis tools like CodeQL (Python) and Sorald (Java) accepted in FSE 2024! Thanks to all the collaborators for the great effort 👍@FSEconf#FSE2024
Pre-print: https://t.co/nzEJRsrNkp
CodePlan is accepted at FSE 2024!
We frame repository level coding as a planning problem over local edits and demonstrate how it can be solved using LLMs + static analysis.
LLMs are good at localized coding tasks. What if a task spans multiple inter-dependent files? These “repository-level coding tasks” cannot be solved directly using LLMs. We formulate these as a planning problem and design a task-agnostic, neuro-symbolic framework called CodePlan.
At #NeurIPS2023 and interested in automating repository level coding with LLMs?
I'll be at our poster today on CodePlan at the Foundation Models for Decision Making Workshop!
Venue: Hall E2 till 5:30 PM
LLMs are good at localized coding tasks. What if a task spans multiple inter-dependent files? These “repository-level coding tasks” cannot be solved directly using LLMs. We formulate these as a planning problem and design a task-agnostic, neuro-symbolic framework called CodePlan.
LLMs are good at localized coding tasks. What if a task spans multiple inter-dependent files? These “repository-level coding tasks” cannot be solved directly using LLMs. We formulate these as a planning problem and design a task-agnostic, neuro-symbolic framework called CodePlan.
How large is the Indian market for B2C tech businesses in terms of users who can generate revenue?
Maybe 15 crores max!
Here's why, with Fintech as a reference, since some data is available. I guess it is important to know this, so we can all be rationally optimistic. 1/11
It's time for another 🧵
IIT GIRLS: How women students at IIT Bombay in the 70s were radicalised by the sexism they faced on campus. And went on to change science in India forever.
1/n] @SforAiDL LRG (https://t.co/CHgjbNrmWR) was established a couple years ago by a bunch of undergrad #NLProc enthusiasts from @BITSPilaniGoa. I am glad to share that the members from the group will be presenting **4** published works at @emnlpmeeting this year: