Hi Yadnyesh Here! I am an aspiring ML researcher interested in both the foundations and the frontiers of AI. My work is motivated by questions around reasoning, reinforcement learning, post-training, ML systems, agentic systems, mechanistic interpretability, alignment, scientific machine learning and large foundation models. I am particularly excited by the challenge of designing AI systems that are more interpretable, efficient and scalable, especially when they can contribute to scientific progress and meaningful practical applications.
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Exponential Security Labs
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09:19
(UTC +05:30) - @novasarc01
- https://ydnyshhh.github.io/
Highlights
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rlvr-gym
rlvr-gym PublicRLVR-Gym is a procedural environment generation library for verifiable reasoning and decision tasks, designed for RLVR, post-training research and structured evaluation. It generates formal, reprod…
Python
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rewardhack-gym
rewardhack-gym Publicrewardhack-gym is a gym-style package for constructing and analyzing verifiable agent environments with controllable proxy-objective mismatch, designed for reward hacking, post-training and mechani…
Python
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synthetic-workspace-gym
synthetic-workspace-gym PublicSynthetic Workspace Gym is a modular framework for generating executable synthetic workspace environments for agents, with hidden evaluators, controllable difficulty and full trajectory logging. It…
Python
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trace2eval
trace2eval PublicTrace2Eval is a local-first Python toolkit for turning failed long-horizon coding-agent runs into small, executable regression evals.
Python
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moral-mechinterp
moral-mechinterp Publicmoral-mechinterp is a reproducible research repo for studying how reward-adapted Qwen agents behave on the GT-HarmBench dataset, and where those behavioral differences appear inside the model.
Python
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