Papers by Inderjeet Singh
DIESEL: A Lightweight Inference-Time Safety Enhancement for Language Models (2025.findings-acl)
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| Challenge: | Large language models generate outputs that are not aligned with human values, such as toxic content, malicious use cases, and vulnerabilities to adversarial jailbreak attacks. |
| Approach: | They propose a lightweight inference-guidance technique that can be seamlessly integrated into any autoregressive LLM to semantically filter undesirable content during generation. |
| Outcome: | The proposed technique can be integrated into any autoregressive LLM to semantically filter undesirable content during generation. |
TFDP: Token-Efficient Disparity Audits for Autoregressive LLMs via Single-Token Masked Evaluation (2025.emnlp-main)
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| Challenge: | Existing methods for auditing autoregressive Large Language Models for disparities are limited and expensive. |
| Approach: | They propose a method to detect disparities in autoregressive Large Language Models by token querying . they propose 'token-focused disparity probing' to measure disparities between sentence pairs . |
| Outcome: | The proposed method detects disparities with 42 times fewer output tokens than previous methods. |