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20202026
most citedUncertainty-Aware Reliable Text Classification

26 citations · 38 across the 16 of their papers we have counts for

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Showing 2026Show all

9 papers · 1 filter

cs.CL2026

The Evaluator Is Part of the Experiment: Measuring Open-Ended LLM Conformity

Alicia Guerra, Yibo Hu

Prior work on LLM conformity largely measures discrete answer flips under verifiable labels. Open-ended revisions require a different measurement strategy because answer quality is…

cs.CL2026

Social Pressure Breaks Majority Voting in LLM Safety Panels

Yibo Hu, Jiaming Qu

Large language models (LLMs) are increasingly used to detect unsafe content. A common approach is to combine judgments from a panel of models to correct individual mistakes, but th…

cs.CR2026

Early Detection of Distributed Backdoors in Multi-Agent LLM Systems: A Characterization Study

Diego Fernandez Arias, Dev Prashant Mistry, Ren Wang +1

Multi-agent LLM systems can be attacked by a payload that no single agent ever holds in full: several poisoned tools each hide one encrypted fragment, spreading them across several…

cs.CR2026

When Local Monitors Miss Compositional Harm: Diagnosing Distributed Backdoors in Multi-Agent Systems

Yibo Hu, Ren Wang

As multi-agent, tool-using LLM systems are deployed, a common safety net is a runtime monitor that checks each message, tool call, or step on its own. We show this net has a fundam…

cs.CL2026

Most LLM Conformity Needs No Speaker: Measuring the Speaker-Free Floor in Peer-Pressure Benchmarks

Yibo Hu, Jiaming Qu

LLM conformity is often used to describe cases where a model changes a correct answer toward a peer or group response. We show that most of this apparent conformity survives even a…

cs.CL2026

Easier to Mislead Than to Correct: Harmful and Beneficial Revision in LLM Conformity

Jiaming Qu, Lucheng Fu, Yibo Hu

Large language models are increasingly used in multi-agent systems, where they see and respond to other agents' answers. A key risk is conformity: a model may abandon its own answe…

cs.SE2026

When Surface Form Changes Moderation Decisions: A Paired Study of Code-Mixed Workflow Instability

Suraj Babu Thimma Krishnaram, Yibo Hu, Karthikeyan Saravanan

Hate moderation is often evaluated as classification on clean English inputs, but deployed systems must route content to actions such as ALLOW, FLAG, or REVIEW. We study how this w…

cs.CL2026

Can I Take Another Dose? Evaluating LLM Decision-Making Under Temporal Uncertainty in OTC Dosing QA

Maroof Kousar, Yibo Hu

Large language models (LLMs) are increasingly used for everyday health questions, including whether a user can safely take another dose of an over-the-counter (OTC) medication. Yet…

cs.CL2026

When Better Codebooks Are Not Enough: Predictive Performance and Behavioral Reliability in LLM Political Event Coding

Zixian He, Bharath Raahul Murugesan, Patrick Brandt +1

High accuracy does not necessarily make an LLM a faithful coder. This issue matters because many social-science studies rely on expert-written codebooks to turn text into structure…