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20232026
most citedA Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

222 citations · 328 across the 139 of their papers we have counts for

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Showing 2026 · cs.CLShow all

13 papers · 2 filters

cs.CL2026

Swiss-Knife: A Framework for Reconfigurable Externalised Multi-Objective Alignment at Decode Time

Agnibh Karmakar, Mayur Parvatikar, Shreyash Dhoot +5

Decode-time alignment methods steer a frozen language model by scoring candidate continuations with an external reward and selecting the maximiser. We argue that this shared design…

cs.CL2026

Khondo: A Multimodal Benchmark for Document Packet Splitting of Bangla Forms

Abu Tyeb Azad, Fahim Ahmed, Ishita Sur Apan +7

Document packets, multiple documents concatenated into a single file, are common in government and administrative workflows, yet splitting them into their constituent documents is…

cs.CL2026

BaFCo: A Document Understanding Benchmark for Complex Bangla Form Comprehension

Abu Tyeb Azad, Ishita Sur Apan, Fahim Ahmed +8

Document comprehension is a challenging yet impactful task for Multimodal Large Language Models, especially as these systems see growing adoption in real-world, human-centric appli…

cs.CL2026

RECOM: A Validity Discrimination Tradeoff in Automatic Metrics for Open Ended Reddit Question Answering

Pushwitha Krishnappa, Amit Das, Vinija Jain +2

Automatic metrics are the default for evaluating LLM-generated text, yet a metric is quietly asked to do two jobs: tell genuine content alignment from surface coincidence (validity…

cs.CL2026

MENTIS: What Belief Changes Under Alignment? Measuring Multi-Scale Latent Torsion in Language Models

Partha Pratim Saha, Samarth Raina, Mayur Parvatikar +4

Preference alignment has substantially improved the observable behavior of large language models, yet it remains unclear what alignment changes internally. Aligned systems still fa…

cs.CL2026

Linear Probes Detect Task Format, Not Reasoning Mode in Language Model Hidden States

Subramanyam Sahoo, Vinija Jain, Aman Chadha +1

Linear probing of large language model (LLM) hidden states is widely used to claim that models learn distinct representations for different reasoning types. We test this by probing…