3 citations · 4 across the 10 of their papers we have counts for
10 papers
BabelArena: A Large-Scale Multilingual Benchmark for LLM Agents
Peng Kuang, Yuchun Fan, Jiangnan Li +7
Large language model (LLM) agents increasingly execute multi-step workflows through tool use and interaction with users and environments. However, current agent evaluations are lar…
Liaozhai through the Looking-Glass: On Paratextual Explicitation of Culture-Bound Terms in Machine Translation
Sherrie Shen, Weixuan Wang, Alexandra Birch
The faithful transfer of contextually-embedded meaning continues to challenge contemporary machine translation (MT), particularly in the rendering of culture-bound terms--expressio…
Learning to Summarize by Learning to Quiz: Adversarial Agentic Collaboration for Long Document Summarization
Weixuan Wang, Minghao Wu, Barry Haddow +1
Long document summarization remains a significant challenge for current large language models (LLMs), as existing approaches commonly struggle with information loss, factual incons…
ExpertSteer: Intervening in LLMs through Expert Knowledge
Weixuan Wang, Minghao Wu, Barry Haddow +1
Large Language Models (LLMs) exhibit remarkable capabilities across various tasks, yet guiding them to follow desired behaviours during inference remains a significant challenge. A…
HBO: Hierarchical Balancing Optimization for Fine-Tuning Large Language Models
Weixuan Wang, Minghao Wu, Barry Haddow +1
Fine-tuning large language models (LLMs) on a mixture of diverse datasets poses challenges due to data imbalance and heterogeneity. Existing methods often address these issues acro…
The Bitter Lesson Learned from 2,000+ Multilingual Benchmarks
Minghao Wu, Weixuan Wang, Sinuo Liu +7
As large language models (LLMs) continue to advance in linguistic capabilities, robust multilingual evaluation has become essential for promoting equitable technological progress.…
PredicateFix: Repairing Static Analysis Alerts with Bridging Predicates
Yuan-An Xiao, Weixuan Wang, Dong Liu +3
Fixing static analysis alerts in source code with Large Language Models (LLMs) is becoming increasingly popular. However, LLMs often hallucinate and perform poorly for complex and…
Demystifying Multilingual Chain-of-Thought in Process Reward Modeling
Weixuan Wang, Minghao Wu, Barry Haddow +1
Large language models (LLMs) are designed to perform a wide range of tasks. To improve their ability to solve complex problems requiring multi-step reasoning, recent research lever…
LF-Steering: Latent Feature Activation Steering for Enhancing Semantic Consistency in Large Language Models
Jingyuan Yang, Rongjun Li, Weixuan Wang +3
Large Language Models (LLMs) often generate inconsistent responses when prompted with semantically equivalent paraphrased inputs. Recently, activation steering, a technique that mo…
Assessing the Reliability of Large Language Model Knowledge
Weixuan Wang, Barry Haddow, Alexandra Birch +1
Large language models (LLMs) have been treated as knowledge bases due to their strong performance in knowledge probing tasks. LLMs are typically evaluated using accuracy, yet this…