6 papers · 1 filter
Transactional Attention: Semantic Sponsorship for KV-Cache Retention
Abhinaba Basu
At K=16 tokens (0.4% of a 4K context), every existing KV-cache compression method achieves 0% on credential retrieval. The failure mode is dormant tokens: credentials, API keys, an…
Measuring and curing reasoning rigidity: from decorative chain-of-thought to genuine faithfulness
Abhinaba Basu, Pavan Chakraborty
Language models increasingly show their work by writing step-by-step reasoning before answering. But are these steps genuinely used, or is the answer rigid - fixed before reasoning…
Why Agent Caching Fails and How to Fix It: Structured Intent Canonicalization with Few-Shot Learning
Abhinaba Basu
Personal AI agents incur substantial cost via repeated LLM calls. We show existing caching methods fail: GPTCache achieves 37.9% accuracy on real benchmarks; APC achieves 0-12%. Th…
ICE: Intervention-Consistent Explanation Evaluation with Statistical Grounding for LLMs
Abhinaba Basu, Pavan Chakraborty
Evaluating whether explanations faithfully reflect a model's reasoning remains an open problem. Existing benchmarks use single interventions without statistical testing, making it…
When Names Change Verdicts: Intervention Consistency Reveals Systematic Bias in LLM Decision-Making
Abhinaba Basu, Pavan Chakraborty
Large language models (LLMs) are increasingly used for high-stakes decisions, yet their susceptibility to spurious features remains poorly characterized. We introduce ICE-Guard, a…
Contextual StereoSet: Stress-Testing Bias Alignment Robustness in Large Language Models
Abhinaba Basu, Pavan Chakraborty
A model that avoids stereotypes in a lab benchmark may not avoid them in deployment. We show that measured bias shifts dramatically when prompts mention different places, times, or…