3 citations · 9 across the 9 of their papers we have counts for
12 papers
The Imperishable Record, Forgiveness, and the Future of Criminal Justice
Mark Fenwick, Paulius Jurcys, Sebastian Porsdam Mann
Digital technologies can preserve records of wrongdoing indefinitely, and AI can give those records continuing influence over a person's future. We describe this condition as the e…
Beyond Oracle Communication: Benchmarking Interactive Intent Alignment Under Miscommunication and Evolving User Intent
Zheyuan Zhang, Mengyuan Chao, Ke Xiao +5
Modern LLM agents increasingly tackle complex tasks through interactive, long-horizon exchanges with users, while existing benchmarks generally assume that users always accurately…
TraceDance: An Automated System for Building Agent Behavior Benchmarks from Real-World Agent Deployment Traces
Dehai Min, Daoan Zhang, Yiming Zeng +13
An agent can complete a task while exhibiting undesirable behavior during execution. Developers need tests for the specific behaviors encountered in deployment, beyond fixed benchm…
VideoWeaver: Evaluating and Evolving Skills for Agentic Long Video Generation
Jianhui Wei, Jie Tan, Hengchuan Zhu +7
Agentic long video generation requires planning, tool orchestration, and cross-clip coordination over a long horizon. Most existing video agents either rely on static, human-crafte…
FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering
Yichen Li, Zhiting Fan, Ruizhe Chen +4
Large language models (LLMs) are prone to capturing biases from training corpus, leading to potential negative social impacts. Existing prompt-based debiasing methods exhibit insta…
M-MAD: Multidimensional Multi-Agent Debate for Advanced Machine Translation Evaluation
Zhaopeng Feng, Jiayuan Su, Jiamei Zheng +5
Recent advancements in large language models (LLMs) have given rise to the LLM-as-a-judge paradigm, showcasing their potential to deliver human-like judgments. However, in the fiel…
Modality-Fair Preference Optimization for Trustworthy MLLM Alignment
Songtao Jiang, Yan Zhang, Ruizhe Chen +6
Multimodal large language models (MLLMs) have achieved remarkable success across various tasks. However, separate training of visual and textual encoders often results in a misalig…
Ladder: A Model-Agnostic Framework Boosting LLM-based Machine Translation to the Next Level
Zhaopeng Feng, Ruizhe Chen, Yan Zhang +2
General-purpose Large Language Models (LLMs) like GPT-4 have achieved remarkable advancements in machine translation (MT) by leveraging extensive web content. On the other hand, tr…
Med-MoE: Mixture of Domain-Specific Experts for Lightweight Medical Vision-Language Models
Songtao Jiang, Tuo Zheng, Yan Zhang +3
Recent advancements in general-purpose or domain-specific multimodal large language models (LLMs) have witnessed remarkable progress for medical decision-making. However, they are…
How Well Do Text Embedding Models Understand Syntax?
Yan Zhang, Zhaopeng Feng, Zhiyang Teng +2
Text embedding models have significantly contributed to advancements in natural language processing by adeptly capturing semantic properties of textual data. However, the ability o…
Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models
Tingyu Xie, Qi Li, Yan Zhang +2
Exploring the application of powerful large language models (LLMs) on the named entity recognition (NER) task has drawn much attention recently. This work pushes the performance bo…
Empirical Study of Zero-Shot NER with ChatGPT
Tingyu Xie, Qi Li, Jian Zhang +3
Large language models (LLMs) exhibited powerful capability in various natural language processing tasks. This work focuses on exploring LLM performance on zero-shot information ext…