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Conflict-Aware Logit Adapters for Utility-Preserving Anti-Distillation
Quoc Phong Dao, Binh Anh Nguyen, Linh Ngo Van +3
While reasoning traces improve model capability, they also provide supervision signals for downstream distillation. Initial efforts to mitigate this issue rely on decoding-time int…
Route-and-Generate: KL-Regularized Router Improvement for Reasoning Routing in LLMs
Tien-Phat Nguyen, Truong Nguyen, Thanh-Thien Le +4
Large language models often apply complex reasoning indiscriminately, leading to overthinking on simple tasks and underthinking on harder ones. We present Route-and-Generate (Rouge…
HyperProve: Answer-Guided Hypergraph Expansion for Multi-Hop Question Answering
An Nguyen Phu, Dung Nguyen Quang, Luu Hieu An +3
Multi-hop question answering often fails when retrieval treats evidence as isolated matches to the original question, since the facts needed to answer a complex question are usuall…
Beyond Repository Boundaries: Cross-Repository Graph Retrieval for Code Generation
Minh Le-Anh, Nam Le Hai, Quyen Tran +4
Repository-level code generation requires generated code to be compatible not only with the target repository but also with its dependency environment. Existing retrieval-based met…
CRISP: Cliff-awaRe Input-adaptive Sparse Prefilling with Structural-Mass-Motivated Routing
Huu Huy Nguyen, Chien Van Nguyen, Franck Dernoncourt +4
The attention prefilling phase of long-context LLM inference scales quadratically, making self-attention a severe computational bottleneck. Traditional sparse attention methods mit…
XREPOTEST: Benchmarking Multilingual Repository-Level Unit Test Generation for Large Language Models
Dung Le Quang, Dong Cao Van, Nam Le Hai +3
Large language models (LLMs) have shown promise for automated unit test generation, but existing evaluations largely rely on standalone settings and a narrow set of programming lan…
TALAS: Teacher-Anchored Layer Alignment with Adaptive Sharpness-Aware Minimization for Embedding Distillation
Quoc Phong Dao, Hoang Son Nguyen, Pham Khanh Chi +4
Knowledge Distillation (KD) has established itself as a pivotal technique for compressing large pre-trained language models. However, existing methods that force a student to stric…
TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching
Truong Nguyen, Tien-Phat Nguyen, Linh Ngo Van +3
Direct Preference Optimization (DPO) is a widely used RL-free method for aligning language models from pairwise preferences, but it models preferences over full sequences even thou…
LLM-XTM: Enhancing Cross-Lingual Topic Models with Large Language Models
Minh Chu Xuan, Tien-Phat Nguyen, Linh Ngo Van +3
Cross-lingual topic modeling aims to discover shared semantic structures across languages, yet existing models depend on sparse bilingual resources and often yield incoherent or we…
MTA: Multi-Granular Trajectory Alignment for Large Language Model Distillation
Pham Khanh Chi, Quoc Phong Dao, Thuat Nguyen +3
Knowledge distillation is a key technique for compressing large language models (LLMs), but most existing methods align representations at fixed layers or token-level outputs, igno…
SRA: Span Representation Alignment for Large Language Model Distillation
Quoc Phong Dao, Hoang Son Nguyen, Pham Khanh Chi +4
Cross-Tokenizer Knowledge Distillation (CTKD) enables knowledge transfer between a large language model and a smaller student, even when they employ different tokenizers. While exi…
MIPIC: Matryoshka Representation Learning via Self-Distilled Intra-Relational and Progressive Information Chaining
Phung Gia Huy, Hai An Vu, Minh-Phuc Truong +4
Representation learning is fundamental to NLP, but building embeddings that work well at different computational budgets is challenging. Matryoshka Representation Learning (MRL) of…
Selective Off-Policy Reference Tuning with Plan Guidance
Duc Anh Le, Anh Duc, Tien-Phat Nguyen +3
Reinforcement learning with verifiable rewards helps reasoning, but GRPO-style methods stall on hard prompts where all sampled rollouts fail. SORT adds a repair update for those fa…
Do Not Treat Code as Natural Language: Implications for Repository-Level Code Generation and Beyond
Minh Le-Anh, Huyen Nguyen, Khanh An Tran +4
Large language models for code (CodeLLMs) have demonstrated remarkable success in standalone code completion and generation, sometimes even surpassing human performance, yet their…
CTPD: Cross Tokenizer Preference Distillation
Truong Nguyen, Phi Van Dat, Ngan Nguyen +3
While knowledge distillation has seen widespread use in pre-training and instruction tuning, its application to aligning language models with human preferences remains underexplore…