1 citations · 2 across the 32 of their papers we have counts for
8 papers · 1 filter
Event Signature Transfer: Model-Agnostic Forecast Scenario Construction from Historical Events
Karthik Sridhar, Aaditya Jain, Murari Mandal +1
Forecasters often know an event is imminent but not the shape, size, or timing of its effect. We introduce Event Signature Transfer (EST), a training-free, model-agnostic operator…
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…
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…
TSQueryBench: LLM-as-a-Judge for Time Series Explanations
Preetham Sivalingam, Murari Mandal, Dhruv Kumar +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…
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…
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…
Right Prediction, Wrong Reasoning: Uncovering LLM Misalignment in RA Disease Diagnosis
Umakanta Maharana, Sarthak Verma, Avarna Agarwal +4
Large language models (LLMs) offer a promising pre-screening tool, improving early disease detection and providing enhanced healthcare access for underprivileged communities. The e…
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…