1 citations · 2 across the 12 of their papers we have counts for
8 papers · 1 filter
Diversity Combining for Multi-Path LLM Reasoning
Guangsheng Yu, Litianyi Zhang, Qin Wang +5
Multi-path reasoning methods such as self-consistency (SC) sample reasoning paths and choose the most frequent answer. However, their gains quickly plateau as increases, an…
CUNO: Curriculum and Preference Optimization for Stable Graph Unlearning under Mass Deletion
Chenhan Zhang, Ali Braytee, Madhushi Bandara +4
Graph unlearning removes the influence of designated training data from a trained graph model without retraining from scratch. However, existing methods suffer a sharp drop in mode…
En-ViMedNER: An English-Vietnamese Parallel Biomedical Corpus with UMLS Semantic Type Annotations
Nhu Vo, Phuong Nguyen, Nu Uyen Phuong Le +4
Biomedical Named Entity Recognition (NER) is fundamental to healthcare AI applications, including clinical decision support and medical information extraction. While corpora with U…
Sample-Efficient Misconfiguration Classification for Network Resilience in Wireless Communications
Xin Hao, Massimo Piccardi, Chenhan Zhang +4
As modern wireless communication networks grow increasingly complex, network outages driven by the inconsistency between dynamic topologies and protocol configurations have become…
DTO: a Differentiable Training Objective for Effective Counterfactual Story Rewriting
Amelia Girard, Massimo Piccardi
Counterfactual story rewriting is a natural language processing task that requires updating an existing story to reflect a chosen alternative event, yet preserving all the unaffect…
Enhancing Network Resilience via Graph-Based Anomaly Detection in Sovereign Functions
Xin Hao, Wei Ni, Chenhan Zhang +2
Sovereign network functions, e.g., routing protocols, are becoming increasingly complex and susceptible to failures arising from protocol configuration anomalies and anomalous conf…
Pref-CTRL: Preference Driven LLM Alignment using Representation Editing
Imranul Ashrafi, Inigo Jauregi Unanue, Massimo Piccardi
Test-time alignment methods offer a promising alternative to fine-tuning by steering the outputs of large language models (LLMs) at inference time with lightweight interventions on…
ViMedCSS: A Vietnamese Medical Code-Switching Speech Dataset & Benchmark
Tung X. Nguyen, Nhu Vo, Giang-Son Nguyen +6
Code-switching (CS), which is when Vietnamese speech uses English words like drug names or procedures, is a common phenomenon in Vietnamese medical communication. This creates chal…