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Contrastive Chain-of-Thought Prompting. (arXiv:2311.09277v1 [cs.CL]) 

Auto-ICL: In-Context Learning without Human Supervision. (arXiv:2311.09263v1 [cs.LG]) 

In the Red(dit): Social Media and Stock Prices. (arXiv:2311.09252v1 [cs.SI]) 

The Cybersecurity Crisis of Artificial Intelligence: Unrestrained Adoption and Natural Language-Based Attacks. (arXiv:2311.09224v1 [cs.CY]) 

AbsPyramid: Benchmarking the Abstraction Ability of Language Models with a Unified Entailment Graph. (arXiv:2311.09174v2 [cs.CL] UPDATED) 

Factcheck-GPT: End-to-End Fine-Grained Document-Level Fact-Checking and Correction of LLM Output. (arXiv:2311.09000v2 [cs.CL] UPDATED) 

MAgIC: Investigation of Large Language Model Powered Multi-Agent in Cognition, Adaptability, Rationality and Collaboration. (arXiv:2311.08562v2 [cs.CL] UPDATED) 

Are Large Language Models Temporally Grounded?. (arXiv:2311.08398v2 [cs.CL] UPDATED) 

KTRL+F: Knowledge-Augmented In-Document Search. (arXiv:2311.08329v3 [cs.CL] UPDATED) 

Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5?. (arXiv:2311.07587v2 [cs.CL] UPDATED) 

InCA: Rethinking In-Car Conversational System Assessment Leveraging Large Language Models. (arXiv:2311.07469v2 [cs.CL] UPDATED) 

Are We Falling in a Middle-Intelligence Trap? An Analysis and Mitigation of the Reversal Curse. (arXiv:2311.07468v2 [cs.CL] UPDATED) 

Exploring the Dialogue Comprehension Ability of Large Language Models. (arXiv:2311.07194v2 [cs.CL] UPDATED) 

Comparative Multi-View Language Grounding. (arXiv:2311.06694v2 [cs.CL] UPDATED) 

ALYMPICS: Language Agents Meet Game Theory. (arXiv:2311.03220v2 [cs.CL] UPDATED) 

Incorporating Worker Perspectives into MTurk Annotation Practices for NLP. (arXiv:2311.02802v2 [cs.CL] UPDATED) 

Support or Refute: Analyzing the Stance of Evidence to Detect Out-of-Context Mis- and Disinformation. (arXiv:2311.01766v3 [cs.CL] UPDATED) 

Construction Artifacts in Metaphor Identification Datasets. (arXiv:2311.00790v2 [cs.CL] UPDATED) 

DEFT: Data Efficient Fine-Tuning for Large Language Models via Unsupervised Core-Set Selection. (arXiv:2310.16776v3 [cs.CL] UPDATED) 

Evaluating the Symbol Binding Ability of Large Language Models for Multiple-Choice Questions in Vietnamese General Education. (arXiv:2310.12059v3 [cs.CL] UPDATED) 

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