10 papers
FinRT: Distilling Adaptive Red-Teaming Strategies into Reusable Adversarial Generators in Consumer Finance
Rikhiya Ghosh, Himanshu Kumar, Sriram Venkatapathy +3
In regulated industries like consumer finance, seemingly harmless user queries can exploit large language model vulnerabilities, triggering safety failures and pushing responses da…
DP-Rec: Towards Dynamic Patching for Efficient Long-Sequence Recommendation
Dwipam Katariya, Thomas Caputo, Akshat Shreemali +6
Transformers have redefined sequential recommendation by effectively modeling dynamic user behaviors and long-range dependencies. However, they remain inherently inefficient: stand…
QUARTET: Quad-branch cross-Attention and Random-walk Traces for Enhancing Transformers on Relational Graphs
Kyaw Hpone Myint, Nan Jiang, Xiang Li +4
Relational Deep Learning (RDL) models multi-table databases as heterogeneous temporal graphs, and graph transformers currently achieve state-of-the-art performance on benchmarks li…
A Systematic Benchmark of Explainable Methods for Temporal Attribution in Sequential Recommendation Systems
Akash Pandey, Kanisha Shah, Addrish Roy +5
Sequential RecSys are central to modern personalization, exploiting user's historical interaction sequences to drive next-step decisions. Deep learning models, particularly CNN and…
Validity-Aware Jailbreak Evaluation for Large Language Models
Qilong Wu, Sahil Wadhwa, Pranab Mohanty +2
Jailbreak robustness has become central to large language model (LLM) safety evaluation, yet prevailing methodologies rely primarily on refusal behavior, semantic resemblance, and…
REPREC: Representation Driven Parameter-Efficient Recommendation System
Harshini Kavuru, Dwipam Katariya, Giri Iyengar +3
Large language models (LLMs) have been applied to sequential recommendation by incorporating collaborative signals through input conditioning or model adaptation. However, existing…
Workspace Topology as an Attack Vector in Agentic Coding Assistants
Alexandre G. R. Day, Pradeep Yadlapalli, Sriram Venkatapathy +9
Agentic coding assistants are finding widespread use, not just in new code development but in quickly ingesting and leveraging third-party code. This opens up a risk of malicious c…
From Clicks to Intent: Cross-Platform Session Embeddings with LLM-Distilled Taxonomy for Financial Services Recommendations
Dianjing Fan, Yao Li, Kyaw Hpone Myint +4
Sequential user behavior modeling is widely adopted in industrial recommender systems; however, significant gaps remain in financial services, where pre-login web interactions and…
ART: Adaptive Reasoning Trees for Explainable Claim Verification
Sahil Wadhwa, Himanshu Kumar, Guanqun Yang +4
Large Language Models (LLMs) are powerful candidates for complex decision-making, leveraging vast encoded knowledge and remarkable zero-shot abilities. However, their adoption in h…
FinTRec: Transformer Based Unified Contextual Ads Targeting and Personalization for Financial Applications
Dwipam Katariya, Snehita Varma, Akshat Shreemali +3
Transformer-based architectures are widely adopted in sequential recommendation systems, yet their application in Financial Services (FS) presents distinct practical and modeling c…