33 citations · 37 across the 9 of their papers we have counts for
9 papers
Recovering Agentic Sovereignty: Mitigating the Consensus Paradox via Contrastive Epistemic Decoding
Dahlia Shehata, Ming Li
Large language models (LLMs) exhibit a parametric vulnerability to adversarial swarm consensus. To mitigate this sycophancy, we introduce Contrastive Epistemic Decoding (CED), a ze…
The Formalism Trap: Are LLM-as-a-Judge Evaluators Blinded by Consensus Mimicry under Social Load?
Dahlia Shehata, Ming Li
We introduce the \textit{Agentic Formalism Trap} and the Evaluative Dissonance Index (), quantifying how LLM-as-a-Judge systems conflate structural proceduralism with semantic…
The Bystander Effect in Multi-Agent Reasoning: Quantifying Cognitive Loafing in Collaborative Interactions
Dahlia Shehata, Ming Li
Multi-agent systems (MAS) assume that collaborating inherently improves Large Language Model (LLM) reasoning. We challenge this by demonstrating that simulated social pressure trig…
The Inverse-Wisdom Law: Architectural Tribalism and the Consensus Paradox in Agentic Swarms
Dahlia Shehata, Ming Li
As AI transitions toward multi-agent systems (MAS) to solve complex workflows, research paradigms operate on the axiomatic assumption that agent collaboration mirrors the "Wisdom o…
Beyond the Attention Stability Boundary: Agentic Self-Synthesizing Reasoning Protocols
Dahlia Shehata, Ming Li
As LLM agents transition to autonomous digital coworkers, maintaining deterministic goal-directedness in non-linear multi-turn conversations emerged as an architectural bottleneck.…
Rumour Evaluation with Very Large Language Models
Dahlia Shehata, Robin Cohen, Charles Clarke
Conversational prompt-engineering-based large language models (LLMs) have enabled targeted control over the output creation, enhancing versatility, adaptability and adhoc retrieval…
Information Retrieval with Entity Linking
Dahlia Shehata
Despite the advantages of their low-resource settings, traditional sparse retrievers depend on exact matching approaches between high-dimensional bag-of-words (BoW) representations…
Early Stage Sparse Retrieval with Entity Linking
Dahlia Shehata, Negar Arabzadeh, Charles L. A. Clarke
Despite the advantages of their low-resource settings, traditional sparse retrievers depend on exact matching approaches between high-dimensional bag-of-words (BoW) representations…
Unpacking Invisible Work Practices, Constraints, and Latent Power Relationships in Child Welfare through Casenote Analysis
Devansh Saxena, Erina Seh-Young Moon, Dahlia Shehata +1
Caseworkers are trained to write detailed narratives about families in Child-Welfare (CW) which informs collaborative high-stakes decision-making. Unlike other administrative data,…