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From the 1 of 9 linked papers with an AI index.

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9 papers

cs.AR2026

PDAGENT-BENCH: Characterizing, Grounding, and Architecting LLM/VLM Agents for VLSI Physical Design

Qiufeng Li, Rongqian Chen, Quan Cheng +6

The paper presents PDAGENT-BENCH, a benchmark suite and workflow framework for evaluating large language model and vision‑language model agents on VLSI physical design tasks, cover…

cs.AI2026

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts

Sizhe Tang, Guangyu Jiang, Yu Li +3

Large Language Models (LLMs) perform strongly on well-specified reasoning tasks with a feasible answer. However, problems encountered in the open world can become ill-posed due to…

cs.AI2026

IntentScore: Intent-Conditioned Action Evaluation for Computer-Use Agents

Rongqian Chen, Yu Li, Zeyu Fang +3

Computer-Use Agents (CUAs) leverage large language models to execute GUI operations on desktop environments, yet they generate actions without evaluating action quality, leading to…

cs.RO2026

Reasoning Knowledge-Gap in Drone Planning via LLM-based Active Elicitation

Zeyu Fang, Beomyeol Yu, Cheng Liu +5

Human-AI joint planning in Unmanned Aerial Vehicles (UAVs) typically relies on control handover when facing environmental uncertainties, which is often inefficient and cognitively…

cs.RO2026

Knowing When to Ask: Resolving Uncertainty in Human-Robot Joint Planning via Explicit Dialogue and Implicit Intent Cues

Zeyu Fang, Yuxin Lin, Cheng Liu +6

Effective human-robot collaboration in open-world environments requires joint planning under uncertainty about the task, the environment, and the human teammate. Communication is t…

cs.AI2026

Agent Alpha: Tree Search Unifying Generation, Exploration and Evaluation for Computer-Use Agents

Sizhe Tang, Rongqian Chen, Tian Lan

While scaling test-time compute through trajectory-level sampling has significantly improved Graphical User Interface (GUI) agents, the lack of regressive ability prevents the reus…