20 citations · 75 across the 44 of their papers we have counts for
10 papers · 1 filter
Findings of the BlackboxNLP 2025 Shared Task: Localizing Circuits and Causal Variables in Language Models
Dana Arad, Yonatan Belinkov, Hanjie Chen +5
Mechanistic interpretability (MI) seeks to uncover how language models (LMs) implement specific behaviors, yet measuring progress in MI remains challenging. The recently released M…
DeepSport: A Multimodal Large Language Model for Comprehensive Sports Video Reasoning via Agentic Reinforcement Learning
Junbo Zou, Haotian Xia, Zhen Ye +5
Sports video understanding requires perceiving high-speed dynamics, complex rules, and long temporal contexts. Yet, current Multimodal Large Language Models (MLLMs) remain narrowly…
SportR: A Benchmark for Multimodal Large Language Model Reasoning in Sports
Haotian Xia, Haonan Ge, Junbo Zou +16
Deeply understanding sports requires an intricate blend of fine-grained visual perception and rule-based reasoning - a challenge that pushes the limits of current multimodal models…
The Generalization Ridge: Information Flow in Natural Language Generation
Ruidi Chang, Chunyuan Deng, Hanjie Chen
Transformer-based language models have achieved state-of-the-art performance in natural language generation (NLG), yet their internal mechanisms for synthesizing task-relevant info…
Steering Information Utility in Key-Value Memory for Language Model Post-Training
Chunyuan Deng, Ruidi Chang, Hanjie Chen
Recent advancements in language models (LMs) have marked a shift toward the growing importance of post-training. Yet, post-training approaches such as supervised fine-tuning (SFT)…
Learning Distribution-Wise Control in Representation Space for Language Models
Chunyuan Deng, Ruidi Chang, Hanjie Chen
Interventions in language models (LMs) are applied strategically to steer model behavior during the forward pass. Learnable interventions, also known as representation fine-tuning,…
Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models
Yang Sui, Yu-Neng Chuang, Guanchu Wang +9
Large Language Models (LLMs) have demonstrated remarkable capabilities in complex tasks. Recent advancements in Large Reasoning Models (LRMs), such as OpenAI o1 and DeepSeek-R1, ha…
SAFR: Neuron Redistribution for Interpretability
Ruidi Chang, Chunyuan Deng, Hanjie Chen
Superposition refers to encoding representations of multiple features within a single neuron, which is common in deep neural networks. This property allows neurons to combine and r…
Rethinking Diverse Human Preference Learning through Principal Component Analysis
Feng Luo, Rui Yang, Hao Sun +5
Understanding human preferences is crucial for improving foundation models and building personalized AI systems. However, preferences are inherently diverse and complex, making it…
Generative Personality Simulation via Theory-Informed Structured Interview
Pengda Wang, Huiqi Zou, Han Jiang +5
Despite their potential as human proxies, LLMs often fail to generate heterogeneous data with human-like diversity, thereby diminishing their value in advancing social science rese…