8 citations · 17 across the 17 of their papers we have counts for
17 papers
StepAudio 2.5 Technical Report
Bin Lin, Bo Zhao, Boyong Wu +98
Unified audio-language modeling has emerged as a prominent trend in modern speech systems, promising to bring the reasoning capabilities of large language models to auditory tasks.…
Interpretable Discriminative Text Representations via Agreement and Label Disentanglement
Tong Wang, Yiqing Xu, Leo Yang Yang
Interpretable text representations should expose coordinates that are not only predictive, but also meaningful enough for independent auditors to apply. Existing discriminative rep…
SpecX: A Large-Scale Benchmark for Multi-Modal Spectroscopy and Cross-Paradigm Evaluation
Chengrui Xiang, Tengfei Ma, Yujie Chen +3
Existing spectral benchmarks are limited in scale, modality alignment, and evaluation scope, and typically focus on either specialized models or multimodal language models (MLLMs).…
Evaluating Nova 2.0 Lite model under Amazon's Frontier Model Safety Framework
Satyapriya Krishna, Matteo Memelli, Tong Wang +5
Amazon published its Frontier Model Safety Framework (FMSF) as part of the Paris AI summit, following which we presented a report on Amazon's Premier model. In this report, we pres…
LIMI: Less is More for Agency
Yang Xiao, Mohan Jiang, Jie Sun +18
We define Agency as the emergent capacity of AI systems to function as autonomous agents actively discovering problems, formulating hypotheses, and executing solutions through self…
Will Annotators Disagree? Identifying Subjectivity in Value-Laden Arguments
Amir Homayounirad, Enrico Liscio, Tong Wang +2
Aggregating multiple annotations into a single ground truth label may hide valuable insights into annotator disagreement, particularly in tasks where subjectivity plays a crucial r…
Llama See, Llama Do: A Mechanistic Perspective on Contextual Entrainment and Distraction in LLMs
Jingcheng Niu, Xingdi Yuan, Tong Wang +2
We observe a novel phenomenon, contextual entrainment, across a wide range of language models (LMs) and prompt settings, providing a new mechanistic perspective on how LMs become d…
WGSR-Bench: Wargame-based Game-theoretic Strategic Reasoning Benchmark for Large Language Models
Qiyue Yin, Pei Xu, Qiaozhe Li +15
Recent breakthroughs in Large Language Models (LLMs) have led to a qualitative leap in artificial intelligence' s performance on reasoning tasks, particularly demonstrating remarka…
DefenderBench: A Toolkit for Evaluating Language Agents in Cybersecurity Environments
Chiyu Zhang, Marc-Alexandre Cote, Michael Albada +6
Large language model (LLM) agents have shown impressive capabilities in human language comprehension and reasoning, yet their potential in cybersecurity remains underexplored. We i…
The Value of AI Advice: Personalized and Value-Maximizing AI Advisors Are Necessary to Reliably Benefit Experts and Organizations
Nicholas Wolczynski, Maytal Saar-Tsechansky, Tong Wang
Despite advances in AI's performance and interpretability, AI advisors can undermine experts' decisions and increase the time and effort experts must invest to make decisions. Cons…
Beyond Mimicry to Contextual Guidance: Knowledge Distillation for Interactive AI
Tong Wang, K. Sudhir
As large language models increasingly mediate firm - customer interactions, firms face a tradeoff: the most capable models perform well but are costly and difficult to control at s…
Less is More for Improving Automatic Evaluation of Factual Consistency
Tong Wang, Ninad Kulkarni, Yanjun Qi
Assessing the factual consistency of automatically generated texts in relation to source context is crucial for developing reliable natural language generation applications. Recent…
Personalized Path Recourse for Reinforcement Learning Agents
Dat Hong, Tong Wang
This paper introduces Personalized Path Recourse, a novel method that generates recourse paths for a reinforcement learning agent. The goal is to edit a given path of actions to ac…
An Empirical Study of Instruction-tuning Large Language Models in Chinese
Qingyi Si, Tong Wang, Zheng Lin +3
The success of ChatGPT validates the potential of large language models (LLMs) in artificial general intelligence (AGI). Subsequently, the release of LLMs has sparked the open-sour…
Generating Pseudo-labels Adaptively for Few-shot Model-Agnostic Meta-Learning
Guodong Liu, Tongling Wang, Shuoxi Zhang +1
Model-Agnostic Meta-Learning (MAML) is a famous few-shot learning method that has inspired many follow-up efforts, such as ANIL and BOIL. However, as an inductive method, MAML is u…
ProtoryNet - Interpretable Text Classification Via Prototype Trajectories
Dat Hong, Tong Wang, Stephen S. Baek
We propose a novel interpretable deep neural network for text classification, called ProtoryNet, based on a new concept of prototype trajectories. Motivated by the prototype theory…
Annotating High-Level Structures of Short Stories and Personal Anecdotes
Boyang Li, Beth Cardier, Tong Wang +1
Stories are a vital form of communication in human culture; they are employed daily to persuade, to elicit sympathy, or to convey a message. Computational understanding of human na…