6 citations · 12 across the 16 of their papers we have counts for
7 papers · 1 filter
Why Is SHAP Not a Reliable Standalone Explanation Framework for Malware Detection?
Seyedreza Mohseni, Edward Raff, Manas Gaur
Machine learning is widely used for malware detection, but its decisions must be explained. An analyst needs to know whether a model has learned genuine malicious behavior or only…
To Erase, or Not to Erase: Robust Training-Free Concept Erasure with Preservation aware Adaptive Ranked Subspace Expansion
Shaswati Saha, Rajasekhar Anguluri, Manas Gaur
Concept erasure techniques (CETs) edit text-to-image diffusion models to erase undesired targets such as NSFW content or copyrighted styles, while preserving model utility on benig…
Structure-Aware Chunking for Tabular Data in Retrieval-Augmented Generation
Pooja Guttal, Varun Magotra, Vasudeva Mahavishnu +3
Tabular documents such as CSV and Excel files are widely used in enterprise data pipelines, yet existing chunking strategies for retrieval-augmented generation (RAG) are primarily…
Analyzing Chain of Thought (CoT) Approaches in Control Flow Code Deobfuscation Tasks
Seyedreza Mohseni, Sarvesh Baskar, Edward Raff +1
Code deobfuscation is the task of recovering a readable version of a program while preserving its original behavior. In practice, this often requires days or even months of manual…
From Concept-Aligned Tokens to Vulnerable Features: Mechanistic Localization of Jailbreaks
Nilanjana Das, Mathew Dawit, Aman Chadha +1
Jailbreak attacks expose a persistent failure mode in safety-aligned LLMs: models can be pushed into harmful behavior, but the internal representations enabling this shift remain p…
Neurosymbolic Retrievers for Retrieval-augmented Generation
Yash Saxena, Manas Gaur
Retrieval Augmented Generation (RAG) has made significant strides in overcoming key limitations of large language models, such as hallucination, lack of contextual grounding, and i…
IMRNNs: An Efficient Method for Interpretable Dense Retrieval via Embedding Modulation
Yash Saxena, Ankur Padia, Kalpa Gunaratna +1
Interpretability in black-box dense retrievers remains a central challenge in Retrieval-Augmented Generation (RAG). Understanding how queries and documents semantically interact is…