523 citations · 531 across the 8 of their papers we have counts for
9 papers
Don't Mask the Environment: Observation Supervision Changes How Agents Explore Under RL
Juzheng Zhang, Disha Makhija, Manoj Ghuhan Arivazhagan +2
Agent trajectories record what an agent does and what happens next. Yet standard supervised fine-tuning (SFT) applies loss only to agent-authored action tokens, using environment o…
Probing the Prompt KV Cache: Where It Becomes Dispensable
Vinayshekhar Bannihatti Kumar, Manoj Ghuhan Arivazhagan, Disha Makhija +1
Prior KV cache compression schemes empirically demonstrate that the prompt cache is partially redundant during decoding, dropping or summarising entries with little accuracy loss.…
Syntax Without Semantics: Teaching Large Language Models to Code in an Unseen Language
Vinayshekhar Bannihatti Kumar, Disha Makhija, Manoj Ghuhan Arivazhagan +1
Large language models (LLMs) achieve high pass rates on code generation benchmarks, yet whether they can transfer this ability to languages absent from pretraining remains poorly u…
When Facts Change: Probing LLMs on Evolving Knowledge with evolveQA
Nishanth Sridhar Nakshatri, Shamik Roy, Manoj Ghuhan Arivazhagan +3
LLMs often fail to handle temporal knowledge conflicts--contradictions arising when facts evolve over time within their training data. Existing studies evaluate this phenomenon thr…
Neural Breadcrumbs: Membership Inference Attacks on LLMs Through Hidden State and Attention Pattern Analysis
Disha Makhija, Manoj Ghuhan Arivazhagan, Vinayshekhar Bannihatti Kumar +1
Membership inference attacks (MIAs) reveal whether specific data was used to train machine learning models, serving as important tools for privacy auditing and compliance assessmen…
SALAD: Source-free Active Label-Agnostic Domain Adaptation for Classification, Segmentation and Detection
Divya Kothandaraman, Sumit Shekhar, Abhilasha Sancheti +3
We present a novel method, SALAD, for the challenging vision task of adapting a pre-trained "source" domain network to a "target" domain, with a small budget for annotation in the…