An end-to-end scientific claim verification system built on a two-stage fine-tuned DeBERTa-v3-base with retrieval augmentation and explainability. Identified and corrected bilateral data leakage affecting 38.4% of the SciFact development split. Macro-F1: 0.9043 (MultiNLI), 0.8640 (SciFact, oracle), 0.7713 (SciTail, zero-shot). Deployed with FastAPI, Docker, and Vercel; integrates Semantic Scholar retrieval, Integrated Gradients (Captum), and GPT-OSS-20B explanations.

An autonomous agentic system for citation-faithfulness verification, orchestrating dual independent verification (fine-tuned DeBERTa-v3 NLI + zero-shot LLM) with a LangGraph ReAct planner that resolves disagreement via tool use — no human intervention required. Caught a shared-bias case where both verifiers agreed on an incorrect SUPPORT verdict at 0.9931 confidence, and corrected it to NOT_ENOUGH_INFO through autonomous escalation across three bounded agent actions, streamed live via Server-Sent Events.

Diagnosed representation anisotropy in transformer encoder outputs — tracing the cause through recent literature (Godey et al., 2024) — and corrected it via GloVe-based embedding initialization, validated through PCA geometric analysis. Built the full encoder from scratch in NumPy (multi-head self-attention, sinusoidal positional encoding, GELU, layer norm, residual connections, following Vaswani et al. 2017) to get direct inspection and control over the representation space itself.