17 citations · 19 across the 13 of their papers we have counts for
13 papers
BiCAA: Bidirectional Credit Assignment for Search-Augmented Agent
Yibin Huang, Bin Xu, Hailong Cao +1
Multi-step search is a fundamental capability for search agents, enabling them to iteratively acquire, refine, and integrate external evidence for complex reasoning QA. However, va…
Long-form RewardBench: Evaluating Reward Models for Long-form Generation
Hui Huang, Yancheng He, Wei Liu +7
The widespread adoption of reinforcement learning-based alignment highlights the growing importance of reward models. Various benchmarks have been built to evaluate reward models i…
RM-Distiller: Exploiting Generative LLM for Reward Model Distillation
Hongli Zhou, Hui Huang, Wei Liu +8
Reward models (RMs) play a pivotal role in aligning large language models (LLMs) with human preferences. Due to the difficulty of obtaining high-quality human preference annotation…
ToolSample: Dual Dynamic Sampling Methods with Curriculum Learning for RL-based Tool Learning
Zihao Feng, Xiaoxue Wang, Bowen Wu +4
While reinforcement learning (RL) is increasingly used for LLM-based tool learning, its efficiency is often hampered by an overabundance of simple samples that provide diminishing…
Cross-Domain Bilingual Lexicon Induction via Pretrained Language Models
Qiuyu Ding, Zhiqiang Cao, Hailong Cao +1
Bilingual Lexicon Induction (BLI) is generally based on common domain data to obtain monolingual word embedding, and by aligning the monolingual word embeddings to obtain the cross…
Enhancing Large Language Models'Machine Translation via Dynamic Focus Anchoring
Qiuyu Ding, Zhiqiang Cao, Hailong Cao +1
Large language models have demonstrated exceptional performance across multiple crosslingual NLP tasks, including machine translation (MT). However, persistent challenges remain in…
Speculative Decoding Meets Quantization: Compatibility Evaluation and Hierarchical Framework Design
Yudi Zhang, Weilin Zhao, Xu Han +4
Speculative decoding and quantization effectively accelerate memory-bound inference of large language models. Speculative decoding mitigates the memory bandwidth bottleneck by veri…
Empowering LLMs in Task-Oriented Dialogues: A Domain-Independent Multi-Agent Framework and Fine-Tuning Strategy
Zihao Feng, Xiaoxue Wang, Bowen Wu +6
Task-oriented dialogue systems based on Large Language Models (LLMs) have gained increasing attention across various industries and achieved significant results. Current approaches…
Lost in Benchmarks? Rethinking Large Language Model Benchmarking with Item Response Theory
Hongli Zhou, Hui Huang, Ziqing Zhao +10
The evaluation of large language models (LLMs) via benchmarks is widespread, yet inconsistencies between different leaderboards and poor separability among top models raise concern…
Mitigating the Bias of Large Language Model Evaluation
Hongli Zhou, Hui Huang, Yunfei Long +5
Recently, there has been a trend of evaluating the Large Language Model (LLM) quality in the flavor of LLM-as-a-Judge, namely leveraging another LLM to evaluate the current output…
Word Embedding Transformation for Robust Unsupervised Bilingual Lexicon Induction
Hailong Cao, Tiejun Zhao
Great progress has been made in unsupervised bilingual lexicon induction (UBLI) by aligning the source and target word embeddings independently trained on monolingual corpora. The…
Gumbel-Attention for Multi-modal Machine Translation
Pengbo Liu, Hailong Cao, Tiejun Zhao
Multi-modal machine translation (MMT) improves translation quality by introducing visual information. However, the existing MMT model ignores the problem that the image will bring…
Duality Regularization for Unsupervised Bilingual Lexicon Induction
Xuefeng Bai, Yue Zhang, Hailong Cao +1
Unsupervised bilingual lexicon induction naturally exhibits duality, which results from symmetry in back-translation. For example, EN-IT and IT-EN induction can be mutually primal…