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cs.CL2026
The Silent Vote: Improving Zero-Shot LLM Reliability by Aggregating Semantic Neighborhoods
Sanket Badhe, Priyanka Tiwari, Deep Shah
Large Language Models are increasingly used as zero-shot classifiers in complex reasoning tasks. However, standard constrained decoding suffers from a phenomenon we define as Renor…
cs.CL2026
CROP: Token-Efficient Reasoning in Large Language Models via Regularized Prompt Optimization
Deep Shah, Sanket Badhe, Nehal Kathrotia +1
Large Language Models utilizing reasoning techniques improve task performance but incur significant latency and token costs due to verbose generation. Existing automatic prompt opt…
cs.CL2026★ 1 cited
Long-Tail Knowledge in Large Language Models: Taxonomy, Mechanisms, Interventions and Implications
Sanket Badhe, Deep Shah, Nehal Kathrotia
Large language models (LLMs) are trained on web-scale corpora that exhibit steep power-law distributions, in which the distribution of knowledge is highly long-tailed, with most ap…