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20242026
most citedCommonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

14 citations · 14 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CL2026

Do Value Vectors in Deep Layers Need Context from the Residual Stream?

Muyu He, Yuchen Liu, Qingya Huang +1

The success of the transformer architecture is in large part due to its use of attention layers. An attention layer follows the standard neural network paradigm: it takes the resid…

cs.CL2026

: Benchmarking AI Agents for Long-Term Planning and Consistent Execution

Muyu He, Adit Jain, Anand Kumar +4

As LLM agents tackle increasingly complex tasks, a critical question is whether they can maintain strategic coherence over long horizons: planning under uncertainty, learning from…

cs.CL2025

The Valley of Code Reasoning: Scaling Knowledge Distillation of Large Language Models

Muyu He, Muhammad Ali Shafique, Anand Kumar +2

Distilling the thinking traces of a Large Language Model (LLM) with reasoning capabilities into a smaller model has been proven effective. Yet, there is a scarcity of work done on…

cs.CL2025

Vision Language Models Cannot Plan, but Can They Formalize?

Muyu He, Yuxi Zheng, Yuchen Liu +7

The advancement of vision language models (VLMs) has empowered embodied agents to accomplish simple multimodal planning tasks, but not long-horizon ones requiring long sequences of…

cs.CL2025

TurnaboutLLM: A Deductive Reasoning Benchmark from Detective Games

Yuan Yuan, Muyu He, Muhammad Adil Shahid +3

This paper introduces TurnaboutLLM, a novel framework and dataset for evaluating the deductive reasoning abilities of Large Language Models (LLMs) by leveraging the interactive gam…