1 citations · 1 across the 4 of their papers we have counts for
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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…
When Users Are Happy but Agents Are Wrong: Multi-Dimensional Evaluation of Tool-Augmented Dialogue
Tanya Shourya, Yingfan Wang, Zhaoyi Joey Hou +3
Evaluating conversational AI systems that use external tools is challenging, as errors can arise from complex interactions among user, agent, and tools. While existing evaluation m…