Cover Image

Small Encoders Can Rival Large Decoders in Detecting Groundedness

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Abbes, Istabrak, Prato, Gabriele, Fournier, Quentin, Rodriguez, Fernando, Boukhary, Alaa, Elwood, Adam, Chandar, Sarath
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence Information Retrieval Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Zero-Shot Multi-Label Classification of Bangla Documents: Large Decoders Vs. Classic Encoders
by: Sarkar, Souvika, et al.
Published: (2025)

Can Cross Encoders Produce Useful Sentence Embeddings?
by: Ananthakrishnan, Haritha, et al.
Published: (2025)

Can Large Language Models Detect Rumors on Social Media?
by: Liu, Qiang, et al.
Published: (2024)

Seq vs Seq: An Open Suite of Paired Encoders and Decoders
by: Weller, Orion, et al.
Published: (2025)

Wrong Answers Can Also Be Useful: PlausibleQA -- A Large-Scale QA Dataset with Answer Plausibility Scores
by: Mozafari, Jamshid, et al.
Published: (2025)

Clinical Reading Comprehension with Encoder-Decoder Models Enhanced by Direct Preference Optimization
by: Nahian, Md Sultan Al, et al.
Published: (2024)

Linguistic features for sentence difficulty prediction in ABSA
by: Chifu, Adrian-Gabriel, et al.
Published: (2024)

Shallow Cross-Encoders for Low-Latency Retrieval
by: Petrov, Aleksandr V., et al.
Published: (2024)

CoRanking: Collaborative Ranking with Small and Large Ranking Agents
by: Liu, Wenhan, et al.
Published: (2025)

Efficient Knowledge Feeding to Language Models: A Novel Integrated Encoder-Decoder Architecture
by: Kumar, S Santosh, et al.
Published: (2025)

Analyzing the Role of Context in Forecasting with Large Language Models
by: Mutschlechner, Gerrit, et al.
Published: (2025)

Can We Use Large Language Models to Fill Relevance Judgment Holes?
by: Abbasiantaeb, Zahra, et al.
Published: (2024)

Can Small Language Models be Good Reasoners for Sequential Recommendation?
by: Wang, Yuling, et al.
Published: (2024)

LLMEmb: Large Language Model Can Be a Good Embedding Generator for Sequential Recommendation
by: Liu, Qidong, et al.
Published: (2024)

Navigating Tomorrow: Reliably Assessing Large Language Models Performance on Future Event Prediction
by: Nako, Petraq, et al.
Published: (2025)

Detecting Future-related Contexts of Entity Mentions
by: Prashar, Puneet, et al.
Published: (2025)

OpenDecoder: Open Large Language Model Decoding to Incorporate Document Quality in RAG
by: Mo, Fengran, et al.
Published: (2026)

Effect of Document Packing on the Latent Multi-Hop Reasoning Capabilities of Large Language Models
by: Prato, Gabriele, et al.
Published: (2025)

Question Difficulty Estimation for Large Language Models via Answer Plausibility Scoring
by: Mozafari, Jamshid, et al.
Published: (2026)

Hallucination Detection and Evaluation of Large Language Model
by: Zhang, Chenggong, et al.
Published: (2025)

Multi-Granularity Guided Fusion-in-Decoder
by: Choi, Eunseong, et al.
Published: (2024)

DELTA: Pre-train a Discriminative Encoder for Legal Case Retrieval via Structural Word Alignment
by: Li, Haitao, et al.
Published: (2024)

Large Language Models' Detection of Political Orientation in Newspapers
by: Buscemi, Alessio, et al.
Published: (2024)

Entity Disambiguation via Fusion Entity Decoding
by: Wang, Junxiong, et al.
Published: (2024)

Towards Unification of Hallucination Detection and Fact Verification for Large Language Models
by: Su, Weihang, et al.
Published: (2025)

Context-aware Decoding Reduces Hallucination in Query-focused Summarization
by: Xu, Zhichao
Published: (2023)

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms
by: Garcia, Fernando Gabriela, et al.
Published: (2024)

Caraman at SemEval-2026 Task 8: Three-Stage Multi-Turn Retrieval with Query Rewriting, Hybrid Search, and Cross-Encoder Reranking
by: Caraman, David-Maximilian, et al.
Published: (2026)

Signal in the Noise: Decoding the Reality of Airline Service Quality with Large Language Models
by: Dawoud, Ahmed, et al.
Published: (2026)

Planning Ahead in Generative Retrieval: Guiding Autoregressive Generation through Simultaneous Decoding
by: Zeng, Hansi, et al.
Published: (2024)

Gradient Flow of Energy: A General and Efficient Approach for Entity Alignment Decoding
by: Wang, Yuanyi, et al.
Published: (2024)

An Early FIRST Reproduction and Improvements to Single-Token Decoding for Fast Listwise Reranking
by: Chen, Zijian, et al.
Published: (2024)

Generative Dense Retrieval: Memory Can Be a Burden
by: Yuan, Peiwen, et al.
Published: (2024)

SLMRec: Distilling Large Language Models into Small for Sequential Recommendation
by: Xu, Wujiang, et al.
Published: (2024)

Drop your Decoder: Pre-training with Bag-of-Word Prediction for Dense Passage Retrieval
by: Ma, Guangyuan, et al.
Published: (2024)

Set-Aligning Framework for Auto-Regressive Event Temporal Graph Generation
by: Tan, Xingwei, et al.
Published: (2024)

Can LLMs Outshine Conventional Recommenders? A Comparative Evaluation
by: Liu, Qijiong, et al.
Published: (2025)

DeTriever: Decoder-representation-based Retriever for Improving NL2SQL In-Context Learning
by: Feng, Yuxi, et al.
Published: (2024)

AutoSurvey: Large Language Models Can Automatically Write Surveys
by: Wang, Yidong, et al.
Published: (2024)

A Bi-Encoder LSTM Model For Learning Unstructured Dialogs
by: Brahman, Danny, et al.
Published: (2021)