3 citations · 4 across the 28 of their papers we have counts for
25 papers · 1 filter
MAS-OPD: On-Policy Distillation for Multi-agent Systems
Qiyong Zhong, Mao Zheng, Mingyang Song +5
Multi-agent systems (MAS) split a task across specialized roles and are promising on complex tasks, yet a prevailing approach relies on inference-time orchestration alone. General-…
USA: Update-aware SAM for Cross-domain On-Policy Disitllation of Language Agents
Qiyong Zhong, Mao Zheng, Mingyang Song +6
On-policy distillation instils multi-turn agentic reasoning through dense token-level supervision on the student's own trajectories, but a single domain saturates early, so further…
Distill What You Trust: Reliability-Aware Multi-Teacher On-Policy Distillation
Jie Sun, Mao Zheng, Mingyang Song +8
Multi-teacher on-policy distillation allows a student to learn from complementary specialists on its own trajectories. Domain-routed approaches, however, select one teacher per exa…
Simple-OPD: Demystifying Warm-up for On-policy Distillation
Tao Liu, Taiqiang Wu, Mao Zheng +5
On-policy distillation (OPD) trains a student on its own rollouts with token-level supervision from teacher models, but its effectiveness can depend strongly on the warm-up stage b…
EasyOPD: An Easy-to-use On-Policy Distillation Framework for Large Language Models
Jie Sun, Mao Zheng, Mingyang Song +7
Conventional language-model distillation often relies on fixed teacher-generated data, which may not cover the states encountered by an evolving student policy. On-policy distillat…
Memory Beyond Recall: A Dual-Process Cognitive Memory System for Self-Evolving LLM Agents
Tianxiang Fei, Mingyang Song, Mao Zheng +1
Long-term memory for an LLM agent is more than retrieving the right passage at the right time. Current memory systems collapse belief revision, causal coupling, and cross-domain ab…
HardMTBench: Stress-Testing Chinese-English Translation on Knowledge-Intensive Domains
Zheng Li, Mao Zheng, Mingyang Song +1
General-purpose machine translation benchmarks such as FLORES-200 have reached a saturation regime on Chinese-English pairs, where modern large language models cluster within a nar…
IFMTBench: A Comprehensive Benchmark for Multilingual Translation Instruction Following
Mingrui Sun, Mao Zheng, Zheng Li +1
Modern translation workflows demand more than semantic equivalence. Users routinely require models to preserve JSON or HTML schemas, honor curated glossaries, disambiguate with pro…
SimCT: Recovering Lost Supervision for Cross-Tokenizer On-Policy Distillation
Jie Sun, Mao Zheng, Mingyang Song +6
On-policy distillation (OPD) is a standard tool for transferring teacher behavior to a smaller student, but it implicitly assumes that teacher and student predictions are comparabl…
SOD: Step-wise On-policy Distillation for Small Language Model Agents
Qiyong Zhong, Mao Zheng, Mingyang Song +5
Tool-integrated reasoning (TIR) is difficult to scale to small language models due to instability in long-horizon tool interactions and limited model capacity. While reinforcement…
PRISM: Probability Reallocation with In-Span Masking for Knowledge-Sensitive Alignment
Chenning Xu, Mao Zheng, Mingyang Song
Supervised fine-tuning (SFT) with token-level hard labels can amplify overconfident imitation of factually unsupported targets, causing hallucinations that propagate in multi-sente…
Model Merging in the Era of Large Language Models: Methods, Applications, and Future Directions
Mingyang Song, Mao Zheng
Model merging combines the parameters of multiple neural networks into a single model without additional training. As fine-tuned large language models (LLMs) proliferate, merging o…
Beyond the Illusion of Consensus: From Surface Heuristics to Knowledge-Grounded Evaluation in LLM-as-a-Judge
Mingyang Song, Mao Zheng, Chenning Xu
The paradigm of LLM-as-a-judge relies on a critical assumption, namely that high inter-evaluator agreement indicates reliable and objective evaluation. We present two complementary…
CodeDelegator: Mitigating Context Pollution via Role Separation in Code-as-Action Agents
Tianxiang Fei, Cheng Chen, Yue Pan +2
Recent advances in large language models (LLMs) allow agents to represent actions as executable code, offering greater expressivity than traditional tool-calling. However, real-wor…
PodBench: A Comprehensive Benchmark for Instruction-Aware Audio-Oriented Podcast Script Generation
Chenning Xu, Mao Zheng, Mingyu Zheng +1
Podcast script generation requires LLMs to synthesize structured, context-grounded dialogue from diverse inputs, yet systematic evaluation resources for this task remain limited. T…
Walk Before You Run! Concise LLM Reasoning via Reinforcement Learning
Mingyang Song, Mao Zheng
As test-time scaling becomes a pivotal research frontier in Large Language Models (LLMs) development, contemporary and advanced post-training methodologies increasingly focus on ex…
TAT-R1: Terminology-Aware Translation with Reinforcement Learning and Word Alignment
Zheng Li, Mao Zheng, Mingyang Song +1
Recently, deep reasoning large language models(LLMs) like DeepSeek-R1 have made significant progress in tasks such as mathematics and coding. Inspired by this, several studies have…
SSR-Zero: Simple Self-Rewarding Reinforcement Learning for Machine Translation
Wenjie Yang, Mao Zheng, Mingyang Song +2
Large language models (LLMs) have recently demonstrated remarkable capabilities in machine translation (MT). However, most advanced MT-specific LLMs heavily rely on external superv…
FastCuRL: Curriculum Reinforcement Learning with Stage-wise Context Scaling for Efficient Training R1-like Reasoning Models
Mingyang Song, Mao Zheng, Zheng Li +4
Improving training efficiency continues to be one of the primary challenges in large-scale Reinforcement Learning (RL). In this paper, we investigate how context length and the com…
GRP: Goal-Reversed Prompting for Zero-Shot Evaluation with LLMs
Mingyang Song, Mao Zheng, Xuan Luo
Pairwise LLM-as-a-judge evaluation asks the judge to identify the \emph{better} of two candidate answers. We study a one-line modification that asks for the \emph{worse} answer ins…
MiMoTable: A Multi-scale Spreadsheet Benchmark with Meta Operations for Table Reasoning
Zheng Li, Yang Du, Mao Zheng +1
Extensive research has been conducted to explore the capability of Large Language Models (LLMs) for table reasoning and has significantly improved the performance on existing bench…
A Survey of Query Optimization in Large Language Models
Mingyang Song, Mao Zheng
Query Optimization (QO) has become essential for enhancing Large Language Model (LLM) effectiveness, particularly in Retrieval-Augmented Generation (RAG) systems where query qualit…
SS-GEN: A Social Story Generation Framework with Large Language Models
Yi Feng, Mingyang Song, Jiaqi Wang +5
Children with Autism Spectrum Disorder (ASD) often misunderstand social situations and struggle to participate in daily routines. Social Stories are traditionally crafted by psycho…
Can Many-Shot In-Context Learning Help LLMs as Evaluators? A Preliminary Empirical Study
Mingyang Song, Mao Zheng, Xuan Luo +1
Utilizing Large Language Models (LLMs) as evaluators to assess the performance of LLMs has garnered attention. However, this kind of evaluation approach is affected by potential bi…