{"total":28,"rows":[{"id":"2302.04023","title":"A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity","created":"2023-02-08","cited_by_count":894,"area":"lr"},{"id":"2305.07004","title":"Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting","created":"2023-05-11","cited_by_count":165,"area":"lr"},{"id":"2212.00193","title":"Distilling Reasoning Capabilities into Smaller Language Models","created":"2022-12-01","cited_by_count":158,"area":"lr"},{"id":"2305.14536","title":"MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems","created":"2023-05-23","cited_by_count":131,"area":"lr"},{"id":"2412.19442","title":"A Survey on Large Language Model Acceleration based on KV Cache Management","created":"2024-12-27","cited_by_count":131,"area":"lr"},{"id":"2403.09028","title":"ChartInstruct: Instruction Tuning for Chart Comprehension and Reasoning","created":"2024-03-14","cited_by_count":68,"area":"lr"},{"id":"2504.10160","title":"MT-R1-Zero: Advancing LLM-based Machine Translation via R1-Zero-like Reinforcement Learning","created":"2025-04-14","cited_by_count":48,"area":"lr"},{"id":"2407.09136","title":"Stepwise Verification and Remediation of Student Reasoning Errors with Large Language Model Tutors","created":"2024-07-12","cited_by_count":41,"area":"lr"},{"id":"2502.11544","title":"Evaluating o1-Like LLMs: Unlocking Reasoning for Translation through Comprehensive Analysis","created":"2025-02-17","cited_by_count":26,"area":"lr"},{"id":"2311.10797","title":"TaCo: Enhancing Cross-Lingual Transfer for Low-Resource Languages in LLMs through Translation-Assisted Chain-of-Thought Processes","created":"2023-11-17","cited_by_count":19,"area":"lr"},{"id":"2403.03636","title":"SheetAgent: Towards A Generalist Agent for Spreadsheet Reasoning and Manipulation via Large Language Models","created":"2024-03-06","cited_by_count":17,"area":"lr"},{"id":"2305.11662","title":"Separating form and meaning: Using self-consistency to quantify task understanding across multiple senses","created":"2023-05-19","cited_by_count":15,"area":"lr"},{"id":"2309.16090","title":"TPE: Towards Better Compositional Reasoning over Conceptual Tools with Multi-persona Collaboration","created":"2023-09-28","cited_by_count":11,"area":"lr"},{"id":"2504.04152","title":"Rethinking Multilingual Continual Pretraining: Data Mixing for Adapting LLMs Across Languages and Resources","created":"2025-04-05","cited_by_count":10,"area":"lr"},{"id":"2506.15629","title":"Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability","created":"2025-06-18","cited_by_count":10,"area":"lr"},{"id":"2503.03308","title":"The Box is in the Pen: Evaluating Commonsense Reasoning in Neural Machine Translation","created":"2025-03-05","cited_by_count":5,"area":"lr"},{"id":"2507.16809","title":"LingBench++: A Linguistically-Informed Benchmark and Reasoning Framework for Multi-Step and Cross-Cultural Inference with LLMs","created":"2025-07-22","cited_by_count":5,"area":"lr"},{"id":"2503.11348","title":"RESPONSE: Benchmarking the Ability of Language Models to Undertake Commonsense Reasoning in Crisis Situation","created":"2025-03-14","cited_by_count":4,"area":"lr"},{"id":"2505.21172","title":"TAT-R1: Terminology-Aware Translation with Reinforcement Learning and Word Alignment","created":"2025-05-27","cited_by_count":3,"area":"lr"},{"id":"2505.22293","title":"Compensating for Data with Reasoning: Low-Resource Machine Translation with LLMs","created":"2025-05-28","cited_by_count":2,"area":"lr"},{"id":"2510.03093","title":"Revisiting Direct Speech-to-Text Translation with Speech LLMs: Better Scaling than CoT Prompting?","created":"2025-10-03","cited_by_count":2,"area":"lr"},{"id":"2602.03352","title":"PEGRL: Improving Machine Translation by Post-Editing Guided Reinforcement Learning","created":"2026-02-03","cited_by_count":1,"area":"lr"},{"id":"2512.14100","title":"A First-Order Logic-Based Alternative to Reward Models in RLHF","created":"2025-12-16","cited_by_count":0,"area":"lr"},{"id":"2604.15390","title":"Analyzing Chain of Thought (CoT) Approaches in Control Flow Code Deobfuscation Tasks","created":"2026-04-16","cited_by_count":0,"area":"lr"},{"id":"2604.20738","title":"RespondeoQA: a Benchmark for Bilingual Latin-English Question Answering","created":"2026-04-22","cited_by_count":0,"area":"lr"},{"id":"2608.03077","title":"PAMT: Process-Aligned Reinforcement Learning for Multi-Domain Machine Translation","created":"2026-08-04","cited_by_count":0,"area":"lr"},{"id":"2609.26536","title":"Transcribe, Translate, and Optimize: Joint Reward Learning for Speech Translation","created":"2026-09-22","cited_by_count":0,"area":"lr"},{"id":"2609.33742","title":"DuraS2ST: Chain-of-Thought and Reinforcement Learning for Duration-Aligned Speech-to-Speech Translation","created":"2026-09-27","cited_by_count":0,"area":"lr"}],"next_cursor":null}