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WatchTree-19/README.md

Hi, I'm Sandeep

This is my open research page, feel free to reach out by email, if you feel I could help out! (Columbia University, alumnus), UK/US-based.

I place myself as an Methodological researcher with interest in idealogical expansion of emerging areas.

[ What I'm building

  • Independent writing on AI evaluation methodology, observability, and the structural overlap between quant trading and LLM eval.
  • Asymmetric-information solutions in ML evaluation, surfacing what labs know internally about benchmark noise and drift.
  • Calibration tooling for benchmark drift, distinguishing genuine model improvement from eval movement.

[ Currently working on

  • A foundational essay on production observability for LLM agents.
  • A weekly paper digest series on alignment, evaluation methodology, and AI safety research.
  • "Benchmark crowding": mapping factor decay in quant finance to benchmark saturation in LLM evaluation.

[ Around the web

Pinned Loading

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    Measure how much your LLM judges actually agree. Inter-judge agreement metrics for LLM-as-a-judge evaluations.

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  4. EleutherAI/lm-evaluation-harness EleutherAI/lm-evaluation-harness Public

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  5. pola-rs/polars pola-rs/polars Public

    Extremely fast Query Engine for DataFrames, written in Rust

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  6. pixie-io/pixie pixie-io/pixie Public

    Instant Kubernetes-Native Application Observability

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