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most citedNine Ways to Break Copyright Law and Why Our LLM Won't: A Fair Use Aligned Generation Framework

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cs.CL2026

Semantics or Structure? Auditing Text Sensitivity in Multimodal Time-Series Forecasting

Karthik Sridhar, Atharva Gupta, Nishant Pradhan +3

Multimodal time-series forecasting has emerged as a promising paradigm in which natural-language context is expected to improve predictive performance. Recent multimodal foundation…

cs.CL2026

FinBalance: A Multi-Document Accounting Reconciliation Benchmark

Sasank Tumpati, Devansh Agarwal, Ayush Kedia +6

Existing financial-NLP benchmarks mostly evaluate prepared artifacts such as filings, tables, or extracted values. Real accounting begins earlier: source documents must be reconcil…

cs.CL2026

Beyond Accuracy: Diagnosing Algebraic Reasoning Failures in LLMs Across Nine Complexity Dimensions

Parth Patil, Dhruv Kumar, Yash Sinha +1

Algebraic reasoning remains one of the most informative stress tests for large language models, yet current benchmarks provide no mechanism for attributing failure to a specific ca…

cs.CL2026

Measuring Representation Robustness in Large Language Models for Geometry

Vedant Jawandhia, Yash Sinha, Murari Mandal +2

Large language models (LLMs) are increasingly evaluated on mathematical reasoning, yet their robustness to equivalent problem representations remains poorly understood. In geometry…

cs.CL2026

The Compliance Paradox: Semantic-Instruction Decoupling in Automated Academic Code Evaluation

Devanshu Sahoo, Manish Prasad, Vasudev Majhi +5

The rapid integration of Large Language Models (LLMs) into educational assessment rests on the unverified assumption that instruction following capability translates directly to ob…

cs.CL2025

NagaNLP: Bootstrapping NLP for Low-Resource Nagamese Creole with Human-in-the-Loop Synthetic Data

Agniva Maiti, Manya Pandey, Murari Mandal

The vast majority of the world's languages, particularly creoles like Nagamese, remain severely under-resourced in Natural Language Processing (NLP), creating a significant barrier…