11 papers
SpeechGym: An Audio-Native Gym for Training Voice Agents via Reinforcement Learning
Jiajun Fan, Jingyuan Li, Prashanth Gurunath Shivakumar +6
Voice agents must call tools and hold multi-turn dialogue entirely through speech, yet the dominant paradigm trains them in text. Existing frameworks either cascade TTS and ASR aro…
Can We Read the Mind of an Audio LLM? A Verbalizable, Multilingual Middle-Layer Workspace
Jiajun Fan, Jingyuan Li, Prashanth Gurunath Shivakumar +8
An audio language model is a black box in a specific way: we see what it says, never what it works out on the way there, and chain-of-thought monitoring helps only if the model wri…
A Kernel-Clean Lean Mechanization of Classical Lottery in Action and the Wakker--Debreu--Koopmans Representation Layer
Jingyuan Li, Ilia Tsetlin, Fan Wang
We present a Lean 4/Mathlib formalization of the additive representation theory behind Classical Lottery in Action and the Wakker-Debreu-Koopmans (WDK) layer it relies on. Our cent…
STELLAR-koff: A Transfer Learning Model for Protein-Ligand Dissociation Rate Constant Prediction Based on Interaction Landscape
Jingyuan Li
The key to successful drug design lies in the correct comprehension of protein-ligand interactions. Within the current knowledge paragm, these interactions can be described from bo…
Incentivizing Consistent, Effective and Scalable Reasoning Capability in Audio LLMs via Reasoning Process Rewards
Jiajun Fan, Roger Ren, Jingyuan Li +6
The role of reasoning in Audio Large Language Models remains widely underexplored, as introducing a reasoning process often degrades rather than improves performance during inferen…
A Two-step Krasnosel'skii-Mann Algorithm with Adaptive Momentum and Its Applications to Image Denoising and Matrix Completion
Yongxin He, Jingyuan Li, Yizun Lin +1
In this paper, we propose a Two-step Krasnosel'skii-Mann (KM) Algorithm (TKMA) with adaptive momentum for solving convex optimization problems arising in image processing. Such opt…
Quantifying Bounded Rationality: Formal Verification of Simon's Satisficing Through Flexible Stochastic Dominance
Jingyuan Li, Zhou Lin
This paper introduces Flexible First-Order Stochastic Dominance (FFSD), a mathematically rigorous framework that formalizes Herbert Simon's concept of bounded rationality using the…
From Axioms to Algorithms: Mechanized Proofs of the vNM Utility Theorem
Li Jingyuan
This paper presents a comprehensive formalization of the von Neumann-Morgenstern (vNM) expected utility theorem using the Lean 4 interactive theorem prover. We implement the classi…
Online Coreset Selection for Learning Dynamic Systems
Jingyuan Li, Dawei Shi, Ling Shi
With the increasing availability of streaming data in dynamic systems, a critical challenge in data-driven modeling for control is how to efficiently select informative data to cha…
ReLExS: Reinforcement Learning Explanations for Stackelberg No-Regret Learners
Xiangge Huang, Jingyuan Li, Jiaqing Xie
With the constraint of a no regret follower, will the players in a two-player Stackelberg game still reach Stackelberg equilibrium? We first show when the follower strategy is eith…
GLIMMER: Incorporating Graph and Lexical Features in Unsupervised Multi-Document Summarization
Ran Liu, Ming Liu, Min Yu +6
Pre-trained language models are increasingly being used in multi-document summarization tasks. However, these models need large-scale corpora for pre-training and are domain-depend…