:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Li, Yanhong, Yang, Chenghao, Ettinger, Allyson
Format:	Preprint
Published:	2024
Subjects:	Computation and Language
Online Access:	https://arxiv.org/abs/2404.09129
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Experimental Contexts Can Facilitate Robust Semantic Property Inference in Language Models, but Inconsistently
by: Misra, Kanishka, et al.
Published: (2024)

Hindsight is 20/20: Building Agent Memory that Retains, Recalls, and Reflects
by: Latimer, Chris, et al.
Published: (2025)

Cognitive Decision Routing in Large Language Models: When to Think Fast, When to Think Slow
by: Du, Y., et al.
Published: (2025)

The Chameleon's Limit: Investigating Persona Collapse and Homogenization in Large Language Models
by: Xiao, Yunze, et al.
Published: (2026)

ThinkSwitcher: When to Think Hard, When to Think Fast
by: Liang, Guosheng, et al.
Published: (2025)

Think-on-Graph 2.0: Deep and Faithful Large Language Model Reasoning with Knowledge-guided Retrieval Augmented Generation
by: Ma, Shengjie, et al.
Published: (2024)

Learning When to Think While Listening in Large Audio-Language Models
by: Song, Zhiyuan, et al.
Published: (2026)

Thinking Out of Order: When Output Order Stops Reflecting Reasoning Order in Diffusion Language Models
by: Yu, Longxuan, et al.
Published: (2026)

WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models
by: Jiang, Liwei, et al.
Published: (2024)

Think Twice Before Trusting: Self-Detection for Large Language Models through Comprehensive Answer Reflection
by: Li, Moxin, et al.
Published: (2024)

InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language Models
by: Yan, Yuchen, et al.
Published: (2025)

Prejudge-Before-Think: Enhancing Large Language Models at Test-Time by Process Prejudge Reasoning
by: Wang, Jianing, et al.
Published: (2025)

Think-Reflect-Revise: A Policy-Guided Reflective Framework for Safety Alignment in Large Vision Language Models
by: Weng, Fenghua, et al.
Published: (2025)

Think Only When You Need with Large Hybrid-Reasoning Models
by: Jiang, Lingjie, et al.
Published: (2025)

CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay
by: Butt, Natasha, et al.
Published: (2024)

Fast Thinking for Large Language Models
by: Zheng, Haoyu, et al.
Published: (2025)

Retrieval-Augmented Hierarchical in-Context Reinforcement Learning and Hindsight Modular Reflections for Task Planning with LLMs
by: Sun, Chuanneng, et al.
Published: (2024)

AI as Humanity's Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Text
by: Lu, Ximing, et al.
Published: (2024)

Selecting and Merging: Towards Adaptable and Scalable Named Entity Recognition with Large Language Models
by: Ding, Zhuojun, et al.
Published: (2025)

WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs
by: Han, Seungju, et al.
Published: (2024)

When Models Reason in Your Language: Controlling Thinking Language Comes at the Cost of Accuracy
by: Qi, Jirui, et al.
Published: (2025)

The Cost of Thinking: Increased Jailbreak Risk in Large Language Models
by: Yang, Fan
Published: (2025)

AdaptThink: Reasoning Models Can Learn When to Think
by: Zhang, Jiajie, et al.
Published: (2025)

Think Before You Prune: Self-Reflective Structured Pruning for Reasoning Language Models
by: Wang, Ziyan, et al.
Published: (2025)

Chunk-Distilled Language Modeling
by: Li, Yanhong, et al.
Published: (2024)

On the Thinking-Language Modeling Gap in Large Language Models
by: Liu, Chenxi, et al.
Published: (2025)

Re-Initialization Token Learning for Tool-Augmented Large Language Models
by: Li, Chenghao, et al.
Published: (2025)

Assessing the Creativity of Large Language Models: Testing, Limits, and New Frontiers
by: Schapiro, Samuel, et al.
Published: (2026)

Look Again, Think Slowly: Enhancing Visual Reflection in Vision-Language Models
by: Jian, Pu, et al.
Published: (2025)

What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective
by: Li, Ming, et al.
Published: (2024)

Thinking in Many Modes: How Composite Reasoning Elevates Large Language Model Performance with Limited Data
by: Ahmad, Zishan, et al.
Published: (2025)

Think Again! The Effect of Test-Time Compute on Preferences, Opinions, and Beliefs of Large Language Models
by: Kour, George, et al.
Published: (2025)

When Do Tools and Planning Help Large Language Models Think? A Cost- and Latency-Aware Benchmark
by: Ghoshal, Subha, et al.
Published: (2026)

TypedThinker: Diversify Large Language Model Reasoning with Typed Thinking
by: Wang, Danqing, et al.
Published: (2024)

ChiMed 2.0: Advancing Chinese Medical Dataset in Facilitating Large Language Modeling
by: Tian, Yuanhe, et al.
Published: (2025)

When Truth Is Overridden: Uncovering the Internal Origins of Sycophancy in Large Language Models
by: Wang, Keyu, et al.
Published: (2025)

Can Multimodal Large Language Model Think Analogically?
by: Guo, Diandian, et al.
Published: (2024)

Cognitive Overload: Jailbreaking Large Language Models with Overloaded Logical Thinking
by: Xu, Nan, et al.
Published: (2023)

When to Think and When to Look: Uncertainty-Guided Lookback
by: Bi, Jing, et al.
Published: (2025)

When Do Language Models Endorse Limitations on Human Rights Principles?
by: Samway, Keenan, et al.
Published: (2026)