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Lost in the Latent Space: How Code Embeddings Represent Functional Intent and Implementation Fidelity

Paper recorded by Signals 4 on 2026-10-29 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-29 on arXiv · recorded by Signals 4 on 2026-10-30

Category: cs.CL · 自然语言处理 · first seen 2026-10-30

Abstract

Code embedding models have become a key building block for many software engineering applications, yet their internal representations remain poorly understood. Existing evaluations tend to focus on downstream task performance, offering limited insight into whether a single embedding can support both functional abstraction and implementation-sensitive analysis. To address this gap, we present a lar

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#82 most recent of 628 cs.CL papers we have recorded · ↑ newer: Raincheck: Deferred Multimodal Prefill for Efficient Multi-Turn MLLM I · ↓ older: Integrating Heterogeneous Echocardiography AI Outputs in Language Spac
Cite this page: Lost in the Latent Space: How Code Embeddings Represent Functional Intent and Implementation Fidelity: the #82 most recent of 628 cs.CL papers we have recorded (as of 2026-10-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/lost-in-the-latent-space-how-code-embeddings-represent-functional-intent-and-imp.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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