activity
20172026
most citedTo CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning

13 citations · 21 across the 10 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

cs.CL2025

SkillFactory: Self-Distillation For Learning Cognitive Behaviors

Zayne Sprague, Jack Lu, Manya Wadhwa +3

Reasoning models leveraging long chains of thought employ various cognitive skills, such as verification of their answers, backtracking, retrying by an alternate method, and more.…

cs.CL2025

ChartMuseum: Testing Visual Reasoning Capabilities of Large Vision-Language Models

Liyan Tang, Grace Kim, Xinyu Zhao +12

Chart understanding presents a unique challenge for large vision-language models (LVLMs), as it requires the integration of sophisticated textual and visual reasoning capabilities.…

cs.CL2025

EvalAgent: Discovering Implicit Evaluation Criteria from the Web

Manya Wadhwa, Zayne Sprague, Chaitanya Malaviya +3

Evaluation of language model outputs on structured writing tasks is typically conducted with a number of desirable criteria presented to human evaluators or large language models (…

cs.LG2025★ 2 cited

Pairwise or Pointwise? Evaluating Feedback Protocols for Bias in LLM-Based Evaluation

Tuhina Tripathi, Manya Wadhwa, Greg Durrett +1

Large Language Models (LLMs) are widely used as proxies for human labelers in both training (Reinforcement Learning from AI Feedback) and large-scale response evaluation (LLM-as-a-…

cs.CL2025

QUDsim: Quantifying Discourse Similarities in LLM-Generated Text

Ramya Namuduri, Yating Wu, Anshun Asher Zheng +3

As large language models become increasingly capable at various writing tasks, their weakness at generating unique and creative content becomes a major liability. Although LLMs hav…