306 citations · 1.3k across the 118 of their papers we have counts for
121 papers
Bellman Policy Optimization
Zhuoqing Song, Haotian Xu, Xikun Zhang +1
Reinforcement learning with verifiable rewards (RLVR) improves the reasoning capabilities of large language models (LLMs). We introduce Bellman Policy Optimization (BPO), a critic-…
EverMemOS: A Self-Organizing Memory Operating System for Structured Long-Horizon Reasoning
Chuanrui Hu, Xingze Gao, Zuyi Zhou +8
Large Language Models (LLMs) are increasingly deployed as long-term interactive agents, yet their limited context windows make it difficult to sustain coherent behavior over extend…
On the Role of Discreteness in Diffusion LLMs
Ziqi Jin, Bin Wang, Xiang Lin +2
Diffusion models offer appealing properties for language generation, such as parallel decoding and iterative refinement, but the discrete and highly structured nature of text chall…
OpenMMReasoner: Pushing the Frontiers for Multimodal Reasoning with an Open and General Recipe
Kaichen Zhang, Keming Wu, Zuhao Yang +6
Recent advancements in large reasoning models have fueled growing interest in extending such capabilities to multimodal domains. However, despite notable progress in visual reasoni…
LongVT: Incentivizing "Thinking with Long Videos" via Native Tool Calling
Zuhao Yang, Sudong Wang, Kaichen Zhang +8
Large multimodal models (LMMs) have shown great potential for video reasoning with textual Chain-of-Thought. However, they remain vulnerable to hallucinations, especially when proc…
MiroThinker: Pushing the Performance Boundaries of Open-Source Research Agents via Model, Context, and Interactive Scaling
MiroMind Team, Song Bai, Lidong Bing +52
We present MiroThinker v1.0, an open-source research agent designed to advance tool-augmented reasoning and information-seeking capabilities. Unlike previous agents that only scale…
First Try Matters: Revisiting the Role of Reflection in Reasoning Models
Liwei Kang, Yue Deng, Yao Xiao +3
Large language models have recently demonstrated significant gains in reasoning ability, often attributed to their capacity to generate longer chains of thought and engage in refle…
Multi-Agent Tool-Integrated Policy Optimization
Zhanfeng Mo, Xingxuan Li, Yuntao Chen +1
Large language models (LLMs) increasingly rely on multi-turn tool-integrated planning for knowledge-intensive and complex reasoning tasks. Existing implementations typically rely o…
Revisiting Self-Play Preference Optimization: On the Role of Prompt Difficulty
Yao Xiao, Jung-jae Kim, Roy Ka-wei Lee +1
Self-play preference optimization has emerged as a prominent paradigm for aligning large language models (LLMs). It typically involves a language model to generate on-policy respon…
MiroMind-M1: An Open-Source Advancement in Mathematical Reasoning via Context-Aware Multi-Stage Policy Optimization
Xingxuan Li, Yao Xiao, Dianwen Ng +15
Large language models have recently evolved from fluent text generation to advanced reasoning across diverse domains, giving rise to reasoning language models. Among these domains,…
100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language Models
Chong Zhang, Yue Deng, Xiang Lin +8
The recent development of reasoning language models (RLMs) represents a novel evolution in large language models. In particular, the recent release of DeepSeek-R1 has generated wid…
M-Longdoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning Framework
Yew Ken Chia, Liying Cheng, Hou Pong Chan +5
The ability to understand and answer questions over documents can be useful in many business and practical applications. However, documents often contain lengthy and diverse multim…
Can-Do! A Dataset and Neuro-Symbolic Grounded Framework for Embodied Planning with Large Multimodal Models
Yew Ken Chia, Qi Sun, Lidong Bing +1
Large multimodal models have demonstrated impressive problem-solving abilities in vision and language tasks, and have the potential to encode extensive world knowledge. However, it…
Auto-Arena: Automating LLM Evaluations with Agent Peer Battles and Committee Discussions
Ruochen Zhao, Wenxuan Zhang, Yew Ken Chia +3
As LLMs continuously evolve, there is an urgent need for a reliable evaluation method that delivers trustworthy results promptly. Currently, static benchmarks suffer from inflexibi…
LLM-R2: A Large Language Model Enhanced Rule-based Rewrite System for Boosting Query Efficiency
Zhaodonghui Li, Haitao Yuan, Huiming Wang +2
Query rewrite, which aims to generate more efficient queries by altering a SQL query's structure without changing the query result, has been an important research problem. In order…
PuzzleVQA: Diagnosing Multimodal Reasoning Challenges of Language Models with Abstract Visual Patterns
Yew Ken Chia, Vernon Toh Yan Han, Deepanway Ghosal +2
Large multimodal models extend the impressive capabilities of large language models by integrating multimodal understanding abilities. However, it is not clear how they can emulate…
Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models
Chaoqun Liu, Wenxuan Zhang, Yiran Zhao +2
Large language models (LLMs) have demonstrated multilingual capabilities, yet they are mostly English-centric due to the imbalanced training corpora. While prior works have leverag…
AdaMergeX: Cross-Lingual Transfer with Large Language Models via Adaptive Adapter Merging
Yiran Zhao, Wenxuan Zhang, Huiming Wang +2
As an effective alternative to the direct fine-tuning on target tasks in specific languages, cross-lingual transfer addresses the challenges of limited training data by decoupling…
How do Large Language Models Handle Multilingualism?
Yiran Zhao, Wenxuan Zhang, Guizhen Chen +2
Large language models (LLMs) have demonstrated impressive capabilities across diverse languages. This study explores how LLMs handle multilingualism. Based on observed language rat…
Contrastive Chain-of-Thought Prompting
Yew Ken Chia, Guizhen Chen, Luu Anh Tuan +2
Despite the success of chain of thought in enhancing language model reasoning, the underlying process remains less well understood. Although logically sound reasoning appears inher…
Towards Robust Temporal Reasoning of Large Language Models via a Multi-Hop QA Dataset and Pseudo-Instruction Tuning
Qingyu Tan, Hwee Tou Ng, Lidong Bing
Knowledge in the real world is being updated constantly. However, it is costly to frequently update large language models (LLMs). Therefore, it is crucial for LLMs to understand th…
Exploring the Potential of Large Language Models in Computational Argumentation
Guizhen Chen, Liying Cheng, Luu Anh Tuan +1
Computational argumentation has become an essential tool in various domains, including law, public policy, and artificial intelligence. It is an emerging research field in natural…
SOUL: Towards Sentiment and Opinion Understanding of Language
Yue Deng, Wenxuan Zhang, Sinno Jialin Pan +1
Sentiment analysis is a well-established natural language processing task, with sentiment polarity classification being one of its most popular and representative tasks. However, d…
Large Language Models can Contrastively Refine their Generation for Better Sentence Representation Learning
Huiming Wang, Zhaodonghui Li, Liying Cheng +2
Recently, large language models (LLMs) have emerged as a groundbreaking technology and their unparalleled text generation capabilities have sparked interest in their application to…