#benchmark evaluation

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32 papers match

cs.AI2026

AgenticASR: Refining Speech Recognition in Real-World Scenarios via an Agentic Approach

Zixuan Jiang, Binghao Qiang, Jiaying Chi +3

The paper introduces AgenticASR, an architecture that continuously refines speech recognition output to remove disfluencies and preserve speaker intent during live audio streams.

#agentic speech recognition#disfluency removal#online transcription#refiner architecture
cs.AI2026

Albilich: Steerable Proof-State Orchestration for LLM-Based Mathematical Research with CAS Integration

Ting Gong, Michael Ruofan Zeng, Yong Yang

Albilich is an open‑source agentic framework that lets large language models conduct long‑horizon mathematical research by integrating computer algebra systems, literature retrieva…

#mathematical reasoning#large language models#computer algebra systems#proof automation
cs.AI2026

When Specifications Conflict: A Symmetry-Based Framework for Measuring LLM Preferences

Tairan Wang, Liang Zhou, Zikang Zhan +1

The paper presents a symmetry‑based experimental framework for measuring how large language models resolve conflicts between competing specifications, and evaluates systematic pref…

#large language models#conflict resolution#specification analysis#symmetry design
cs.AI2026

Rethinking Inference-Time Scaling in Local Computer-Use Agents: Failure Modes and Compute Tradeoffs

Woongkyu Lee, Jungwook Choi

The paper empirically studies how different inference-time scaling strategies affect the performance and failure modes of locally deployed autonomous computer-use agents under hard…

#autonomous agents#computer-use agents#inference scaling#resource-constrained models
cs.AI2026

How Benchmarks Mis-Score Computer-Use Agents

Zihan Dong, Zhiyuan Ma, Zekun Wang +5

The paper examines how current benchmarks for computer-use agents often give inaccurate scores due to issues in task design, trajectory observation, scoring, and reporting, and pro…

#computer-use agents#benchmark evaluation#reliability#error analysis
cs.AI2026

Evidence-Ledger Adjudication for Claim-Evidence Traceability

Gengyu Chen, Yongjie Yu, Weiling Wang

The paper introduces evidence-ledger adjudication, a workflow that pairs AI‑generated claims with evidence packets, assigns support relations, and routes unsupported or contradicto…

#claim verification#evidence retrieval#AI‑assisted writing#traceability