6 citations · 14 across the 20 of their papers we have counts for
10 papers · 1 filter
ReRank: Listwise Reranking with Reasoning-Conditioned Retrieval Heads
Ruiyi Yan, Zhuoyuan Mao, Yugo Murawaki +1
Attention-based rerankers score each candidate by the attention mass that retrieval heads route to it from the question, but the question, serving as a fixed query, carries limited…
APRiL: An Open-ended Benchmark for Chinese Social Awareness in Large Language Models
Tian Lan, Han Zhang, Shanshan Wang +3
Large language models are increasingly used in social interactions, where appropriate responses require recognizing implicit cues, inferring mental states, identifying conflicts, a…
A Comprehensive Survey on Linguistic Steganography: Methods, Countermeasures, Evaluation, and Challenges
Ruiyi Yan, Chenhui Chu, Zhongliang Yang +1
Linguistic steganography hides secret messages in natural language text. Large language models (LLMs) have reshaped the field, but a systematic account of how these scattered advan…
HiTMS: A High-Throughput Multi-Stream Linguistic Steganography Framework
Ruiyi Yan, Zhongliang Yang, Yugo Murawaki
Generative linguistic steganography conceals secret bits within the sampling randomness of large language models. Existing schemes are single-stream, conveying an entire secret thr…
Dango: A Strictly L1-Only Large Language Model for Studying Second Language Acquisition
Shiho Matta, Yin Jou Huang, Fei Cheng +3
We introduce Dango, a 1.8B-parameter large language model designed for controlled studies of L1-to-L2 (Japanese-to-English) transfer in second language acquisition (SLA). While pre…
Scaling LLM Reasoning from Minimal Labels: A Semi-Supervised Framework with a Lightweight Verifier
Keizo Kato, Chenhui Chu, Yugo Murawaki +1
For the development of Large language models (LLMs), recent approaches to generating pseudo intermediate reasoning have shown remarkable progress. But they typically rely on large…
Anchored Sliding Window: Toward Robust and Imperceptible Linguistic Steganography
Ruiyi Yan, Shiao Meng, Yugo Murawaki
Linguistic steganography based on language models typically assumes that steganographic texts are transmitted without alteration, making them fragile to even minor modifications. W…
Efficient Provably Secure Linguistic Steganography via Range Coding
Ruiyi Yan, Yugo Murawaki
Linguistic steganography involves embedding secret messages within seemingly innocuous texts to enable covert communication. Provable security, which is a long-standing goal and ke…
Can We Trust LLM Detectors?
Jivnesh Sandhan, Harshit Jaiswal, Fei Cheng +1
The rapid adoption of LLMs has increased the need for reliable AI text detection, yet existing detectors often fail outside controlled benchmarks. We systematically evaluate 2 domi…
Persona Jailbreaking in Large Language Models
Jivnesh Sandhan, Fei Cheng, Tushar Sandhan +1
Large Language Models (LLMs) are increasingly deployed in domains such as education, mental health and customer support, where stable and consistent personas are critical for relia…