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20242026
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cs.AI2026

The Complexity Ceiling Benchmark: A Multi-Domain Evaluation of Sequential Reasoning Under Depth Scaling

Shubh Chapra, Dhruv Kumar, Murari Mandal +1

We introduce the Complexity Ceiling Benchmark (CCB), a controlled evaluation of how language-model reasoning decays as the number of required sequential steps grows. CCB fixes the…

cs.AI2026

GITCO: Gated Inference-Time Context Optimization in TSFMs

Manya Pandey, Dhruv Kumar, Murari Mandal +1

Patch-based Time Series Foundation Models (TSFMs) suffer from context poisoning: structurally anomalous patches capture disproportionate attention and silently degrade zero-shot fo…

cs.AI2026

TSQueryBench: LLM-as-a-Judge for Time Series Explanations

Preetham Sivalingam, Murari Mandal, Saurabh Deshpande +1

Natural language explanations of time series data are increasingly produced by foundation models in high stakes domains, making factual correctness critical. Evaluating such explan…

cs.AI2026

When Reject Turns into Accept: Quantifying the Vulnerability of LLM-Based Scientific Reviewers to Indirect Prompt Injection

Devanshu Sahoo, Manish Prasad, Vasudev Majhi +5

Driven by surging submission volumes, scientific peer review has catalyzed two parallel trends: individual over-reliance on LLMs and institutional AI-powered assessment systems. Th…

cs.AI2025

Agents Are All You Need for LLM Unlearning

Debdeep Sanyal, Murari Mandal

Information removal or suppression in large language models (LLMs) is a desired functionality, useful in AI regulation, legal compliance, safety, and privacy. LLM unlearning method…

cs.AI2025

Investigating Pedagogical Teacher and Student LLM Agents: Genetic Adaptation Meets Retrieval Augmented Generation Across Learning Style

Debdeep Sanyal, Agniva Maiti, Umakanta Maharana +4

Effective teaching requires adapting instructional strategies to accommodate the diverse cognitive and behavioral profiles of students, a persistent challenge in education and teac…