Papers by Danush Khanna
Legal Judgment Reimagined: PredEx and the Rise of Intelligent AI Interpretation in Indian Courts (2024.findings-acl)
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| Challenge: | Prediction with Explanation is the largest expert-annotated dataset for legal judgment prediction and explanation in the Indian context . |
| Approach: | They propose to use an annotated legal judgment prediction corpus to improve models' accuracy . they employ transformer-based models tailored for both general and Indian legal contexts . |
| Outcome: | The proposed system improves the accuracy and explanatory depth of models for legal judgments. |
SELF-PERCEPT: Introspection Improves Large Language Models’ Detection of Multi-Person Mental Manipulation in Conversations (2025.acl-short)
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Danush Khanna, Pratinav Seth, Sidhaarth Sredharan Murali, Aditya Kumar Guru, Siddharth Shukla, Tanuj Tyagi, Sandeep Chaurasia, Kripabandhu Ghosh
| Challenge: | Mental manipulation is subtle yet pervasive form of abuse in interpersonal communication, making its detection critical for safeguarding potential victims. |
| Approach: | They propose a dataset of 220 multi-turn, multi-person dialogues balanced between manipulative and non-manipulative interactions drawn from reality shows that mimic real-life scenarios. |
| Outcome: | The proposed framework shows that it can detect multi-person, multi-turn mental manipulation in multi-people conversations. |
DPO Kernels: A Semantically-Aware, Kernel-Enhanced, and Divergence-Rich Paradigm for Direct Preference Optimization (2025.findings-acl)
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Amitava Das, Suranjana Trivedy, Danush Khanna, Yaswanth Narsupalli, Basab Ghosh, Rajarshi Roy, Gurpreet Singh, Vinija Jain, Vasu Sharma, Aishwarya Naresh Reganti, Aman Chadha
| Challenge: | Direct Preference Optimization (DPO) is a cornerstone for preference alignment but is constrained by fixed divergence measures and limited feature transformations. |
| Approach: | They propose a new enhancement of Direct Preference Optimization that integrates kernel methods to overcome these challenges. |
| Outcome: | The proposed model improves divergence measures and features by using kernels . the proposed model achieves state-of-the-art generalization in factuality, safety, reasoning, and instruction following . |
Alignment Quality Index (AQI) : Beyond Refusals: AQI as an Intrinsic Alignment Diagnostic via Latent Geometry, Cluster Divergence, and Layer wise Pooled Representations (2025.emnlp-main)
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Abhilekh Borah, Chhavi Sharma, Danush Khanna, Utkarsh Bhatt, Gurpreet Singh, Hasnat Md Abdullah, Raghav Kaushik Ravi, Vinija Jain, Jyoti Patel, Shubham Singh, Vasu Sharma, Arpita Vats, Rahul Raja, Aman Chadha, Amitava Das
| Challenge: | a new metric measures the quality of large language models (LLMs) that detects hidden misalignments and jailbreak risks. |
| Approach: | They propose a decoding-invariant metric that measures latent safety failures . they propose 'Alignment Quality Index' to measure latent activations in latent space . |
| Outcome: | The proposed metric detects latent safety failures overlooked by behavioral benchmarks and jailbreaks. |