Cover Image

HEFT: A Coarse-to-Fine Hierarchy for Enhancing the Efficiency and Accuracy of Language Model Reasoning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Hill, Brennen
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence Machine Learning 68T07, 68T50, 68T05 I.2.7; I.2.6; C.4
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Mechanistic Analysis of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning
by: Imanov, Olaf Yunus Laitinen
Published: (2026)

Rethinking the Multilingual Reasoning Gap with Layer Swap
by: Lasbordes, Maxence, et al.
Published: (2026)

CLMN: Concept based Language Models via Neural Symbolic Reasoning
by: Yang, Yibo
Published: (2025)

Strategic Doctrine Language Models (sdLM): A Learning-System Framework for Doctrinal Consistency and Geopolitical Forecasting
by: Imanov, Olaf Yunus Laitinen, et al.
Published: (2026)

Harnessing non-adversarial robustness in large language models
by: Zhou, Qinghua, et al.
Published: (2026)

Latent Object Permanence: Topological Phase Transitions, Free-Energy Principles, and Renormalization Group Flows in Deep Transformer Manifolds
by: Alpay, Faruk, et al.
Published: (2026)

Inference acceleration for large language models using "stairs" assisted greedy generation
by: Grigaliūnas, Domas, et al.
Published: (2024)

NOTAI.AI: Explainable Detection of Machine-Generated Text via Curvature and Feature Attribution
by: Breneur, Oleksandr Marchenko, et al.
Published: (2026)

Vis-CoT: A Human-in-the-Loop Framework for Interactive Visualization and Intervention in LLM Chain-of-Thought Reasoning
by: Pather, Kaviraj, et al.
Published: (2025)

Sentiment Analysis of Lithuanian Online Reviews Using Large Language Models
by: Vileikytė, Brigita, et al.
Published: (2024)

Enhancing Ultra-Low-Bit Quantization of Large Language Models Through Saliency-Aware Partial Retraining
by: Cao, Deyu, et al.
Published: (2025)

XAutoLM: Efficient Fine-Tuning of Language Models via Meta-Learning and AutoML
by: Estevanell-Valladares, Ernesto L., et al.
Published: (2025)

mHC-SSM: Manifold-Constrained Hyper-Connections for State Space Language Models with Stream-Specialized Adapters
by: Mutlu, Abdulvahap, et al.
Published: (2026)

CogniLoad: A Synthetic Natural Language Reasoning Benchmark With Tunable Length, Intrinsic Difficulty, and Distractor Density
by: Kaiser, Daniel, et al.
Published: (2025)

AIPsy-Affect: A Keyword-Free Clinical Stimulus Battery for Mechanistic Interpretability of Emotion in Language Models
by: Keeman, Michael
Published: (2026)

Extracting Sentence Embeddings from Pretrained Transformer Models
by: Stankevičius, Lukas, et al.
Published: (2024)

Think-at-Hard: Selective Latent Iterations to Improve Reasoning Language Models
by: Fu, Tianyu, et al.
Published: (2025)

How much do LLMs learn from negative examples?
by: Hamdan, Shadi, et al.
Published: (2025)

ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective
by: Chen, Yihong, et al.
Published: (2022)

Product-of-Experts Training Reduces Dataset Artifacts in Natural Language Inference
by: Mathew, Aby Mammen
Published: (2026)

Do Reasoning Models Enhance Embedding Models?
by: Chan, Wun Yu, et al.
Published: (2026)

When Does Content-Based Routing Work? Representation Requirements for Selective Attention in Hybrid Sequence Models
by: Basu, Abhinaba
Published: (2026)

SafeAnchor: Preventing Cumulative Safety Erosion in Continual Domain Adaptation of Large Language Models
by: Guo, Dongxin, et al.
Published: (2026)

Who's Asking? Investigating Bias Through the Lens of Disability Framed Queries in LLMs
by: Hari, Vishnu, et al.
Published: (2025)

Breaking to Build: A Threat Model of Prompt-Based Attacks for Securing LLMs
by: Hill, Brennen, et al.
Published: (2025)

From Noise to Diversity: Random Embedding Injection in LLM Reasoning
by: Kim, Heejun, et al.
Published: (2026)

No Memorization, No Detection: Output Distribution-Based Contamination Detection in Small Language Models
by: Sela, Omer
Published: (2026)

Sliced-Wasserstein Distribution Alignment Loss Improves the Ultra-Low-Bit Quantization of Large Language Models
by: Cao, Deyu, et al.
Published: (2026)

Beyond Accuracy: Decomposing the Reasoning Efficiency of LLMs
by: Kaiser, Daniel, et al.
Published: (2026)

Linguistic Collapse: Neural Collapse in (Large) Language Models
by: Wu, Robert, et al.
Published: (2024)

How Pruning Reshapes Features: Sparse Autoencoder Analysis of Weight-Pruned Language Models
by: Borobia, Hector, et al.
Published: (2026)

lmfaoooo at SemEval-2026 Task 1: Humor Is an Audience. Preference Modeling for Constrained Humor Generation
by: Tikhonov, Alexey, et al.
Published: (2026)

SAGE: Sign-Adaptive Gradient for Memory-Efficient LLM Optimization
by: Lee, Wooin, et al.
Published: (2026)

MAcPNN: Mutual Assisted Learning on Data Streams with Temporal Dependence
by: Giannini, Federico, et al.
Published: (2026)

ProbeScale: Probing Analysis to Optimize Neural Scaling Laws for Efficient Small Language Model Inference
by: Das, Sourav
Published: (2026)

Fine-tuning of Large Language Models for Constituency Parsing Using a Sequence to Sequence Approach
by: Delgado, Francisco Jose Cortes, et al.
Published: (2025)

Unpacking Hateful Memes: Presupposed Context and False Claims
by: Cai, Weibin, et al.
Published: (2025)

The Geometry of Persona: Disentangling Personality from Reasoning in Large Language Models
by: Wang, Zhixiang
Published: (2025)

Transactional Attention: Semantic Sponsorship for KV-Cache Retention
by: Basu, Abhinaba
Published: (2026)

Mitigating Position-Shift Failures in Text-Based Modular Arithmetic via Position Curriculum and Template Diversity
by: Yudin, Nikolay
Published: (2026)