Who cites «Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences»

299 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

A Survey on Evaluation of LLM-based Agents — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
BizCompass: Benchmarking the Reasoning Capabilities of LLMs in Business Knowledge and Applications — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
Charting the European LLM Benchmarking Landscape: A New Taxonomy and Registry — 2026 · Proceedings of Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities (LLMs4SSH) @ LREC 2026
ChunkFT: Byte-Streamed Optimization for Memory-Efficient Full Fine-Tuning — 2026 · arXiv:2605.21177
Decompose-and-Refine: Structured Legal Question Answering with Parametric Retrieval — 2026 · arXiv:2605.24454
High-Throughput and Memory-Efficient Zeroth-Order Fine-tuning LLMs with Distributed Parallel Computing — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
PEFT-Bench: A Parameter-Efficient Fine-Tuning Methods Benchmark — 2026 · Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
PEFT-Factory: Unified Parameter-Efficient Fine-Tuning of Autoregressive Large Language Models — 2026 · Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations)
Serbian SuperGLUE: Towards an Evaluation Benchmark for South Slavic Language Models — 2026 · Proceedings of the Second Workshop on Language Models for Low-Resource Languages (LoResLM 2026)
Ultra-Low-Dimensional Prompt Tuning via Random Projection — 2026 · Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
Universally Empowering Zeroth-Order Optimization via Adaptive Layer-wise Sampling — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
ZOCheck: CPU-Shadow Checkpointing for Zeroth-Order LLM Fine-Tuning — 2026 · arXiv:2609.27189
ltzGLUE: Luxembourgish General Language Understanding Evaluation — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
Beyond Output Matching: Bidirectional Alignment for Enhanced In-Context Learning — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
BiLD: Bi-directional Logits Difference Loss for Large Language Model Distillation — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
Bidirectional Emotional Influence in Human-LLM Interaction: Empirical Analysis and Methodological Framework — 2025 · Proceedings of the Eleventh Italian Conference on Computational Linguistics (CLiC-it 2025)
CTCC: A Robust and Stealthy Fingerprinting Framework for Large Language Models via Cross-Turn Contextual Correlation Backdoor — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Calibrating LLM Confidence by Probing Perturbed Representation Stability — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Can Stories Help LLMs Reason? Curating Information Space Through Narrative — 2025 · Proceedings of the 2nd Workshop on Analogical Abstraction in Cognition, Perception, and Language (Analogy-Angle II)
CausalEval: Towards Better Causal Reasoning in Language Models — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Dynamic Task Vector Grouping for Efficient Multi-Task Prompt Tuning — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Efficient and Effective Prompt Tuning via Prompt Decomposition and Compressed Outer Product — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
EverTracer: Hunting Stolen Large Language Models via Stealthy and Robust Probabilistic Fingerprint — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
FPEdit: Robust LLM Fingerprinting through Localized Parameter Editing — 2025 · arXiv:2508.02092
First Attentions Last: Better Exploiting First Attentions for Efficient Transformer Training — 2025 · arXiv:2510.14614
Harmony in Divergence: Towards Fast, Accurate, and Memory-efficient Zeroth-order LLM Fine-tuning — 2025 · arXiv:2502.03304
Investigating Critical Period Effects in Language Acquisition through Neural Language Models — 2025 · Transactions of the Association for Computational Linguistics
KerZOO: Kernel Function Informed Zeroth-Order Optimization for Accurate and Accelerated LLM Fine-Tuning — 2025 · arXiv:2505.18886
Learning to Select In-Context Demonstration Preferred by Large Language Model — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
LoCt-Instruct: An Automatic Pipeline for Constructing Datasets of Logical Continuous Instructions — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
MDPO: Customized Direct Preference Optimization with a Metric-based Sampler for Question and Answer Generation — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
MEPT: Mixture of Expert Prompt Tuning as a Manifold Mapper — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
MEraser: An Effective Fingerprint Erasure Approach for Large Language Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
MUZO: Leveraging Multiple Queries and Momentum for Zeroth-Order Fine-Tuning of Large Language Models — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Machine Translation Meta Evaluation through Translation Accuracy Challenge Sets — 2025 · Computational Linguistics
Once Upon a Time: Interactive Learning for Storytelling with Small Language Models — 2025 · Proceedings of the First BabyLM Workshop
Optimizing Pre-Training Data Mixtures with Mixtures of Data Expert Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Piecing It All Together: Verifying Multi-Hop Multimodal Claims — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
Position Really Matters: Towards a Holistic Approach for Prompt Tuning — 2025 · Findings of the Association for Computational Linguistics: NAACL 2025
RecombiText: Compositional Data Augmentation for Enhancing LLM Pre-Training Datasets in Low-Resource Scenarios — 2025 · Proceedings of the First BabyLM Workshop
SCOP: Evaluating the Comprehension Process of Large Language Models from a Cognitive View — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
SSMLoRA: Enhancing Low-Rank Adaptation with State Space Model — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Self-Adjust Softmax — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Should I Share this Translation? Evaluating Quality Feedback for User Reliance on Machine Translation — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Single layer tiny Co4 outpaces GPT-2 and GPT-BERT — 2025 · Proceedings of the First BabyLM Workshop
Unlocking the Effectiveness of LoRA-FP for Seamless Transfer Implantation of Fingerprints in Downstream Models — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
ZO2: Scalable Zeroth-Order Fine-Tuning for Extremely Large Language Models with Limited GPU Memory — 2025 · arXiv:2503.12668
A Multi-Task Embedder For Retrieval Augmented LLMs — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
A linguistically-motivated evaluation methodology for unraveling model's abilities in reading comprehension tasks — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
ACCEPT: Adaptive Codebook for Composite and Efficient Prompt Tuning — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models — 2024 · arXiv:2410.06441
An Information-Theoretic Approach to Analyze NLP Classification Tasks — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model — 2024 · arXiv:2402.07827
BiKT: Enabling Bidirectional Knowledge Transfer Between Pretrained Models and Sequential Downstream Tasks — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
CARE: A Clue-guided Assistant for CSRs to Read User Manuals — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Calibration-Tuning: Teaching Large Language Models to Know What They Don''t Know — 2024 · Proceedings of the 1st Workshop on Uncertainty-Aware NLP (UncertaiNLP 2024)
Continual Learning of Large Language Models: A Comprehensive Survey — 2024 · arXiv:2404.16789
Contrastive Instruction Tuning — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
Explaining and Improving Contrastive Decoding by Extrapolating the Probabilities of a Huge and Hypothetical LM — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Full Parameter Fine-tuning for Large Language Models with Limited Resources — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
GPT or BERT: why not both? — 2024 · The 2nd BabyLM Challenge at the 28th Conference on Computational Natural Language Learning
Goodhart's Law Applies to NLP's Explanation Benchmarks — 2024 · Findings of the Association for Computational Linguistics: EACL 2024
HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
HiRE: High Recall Approximate Top-$k$ Estimation for Efficient LLM Inference — 2024 · arXiv:2402.09360
In-context Learning with Retrieved Demonstrations for Language Models: A Survey — 2024 · arXiv:2401.11624
Initialization of Large Language Models via Reparameterization to Mitigate Loss Spikes — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Instruction Pre-Training: Language Models are Supervised Multitask Learners — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Instructional Fingerprinting of Large Language Models — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Is Prompt Transfer Always Effective? An Empirical Study of Prompt Transfer for Question Answering — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)
Kraken: Inherently Parallel Transformers For Efficient Multi-Device Inference — 2024 · arXiv:2408.07802
Large Language Models Must Be Taught to Know What They Don't Know — 2024 · arXiv:2406.08391
Large Language Models: A Survey — 2024 · arXiv:2402.06196
Learning to Compress Prompt in Natural Language Formats — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Learning to Retrieve In-Context Examples for Large Language Models — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
Light-PEFT: Lightening Parameter-Efficient Fine-Tuning via Early Pruning — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style Plugin — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
LoRASC: Expressive and Generalizable Low-rank Adaptation for Large Models via Slow Cascaded Learning — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
Multi-Task Inference: Can Large Language Models Follow Multiple Instructions at Once? — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Multi-Task Learning with Adapters for Plausibility Prediction: Bridging the Gap or Falling into the Trenches? — 2024 · Proceedings of the Fifth Workshop on Insights from Negative Results in NLP
Multi-mask Prefix Tuning: Applying Multiple Adaptive Masks on Deep Prompt Tuning — 2024 · Proceedings of the 38th Pacific Asia Conference on Language, Information and Computation
MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries — 2024 · arXiv:2401.15391
On Evaluating Explanation Utility for Human-AI Decision Making in NLP — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
On the Universal Truthfulness Hyperplane Inside LLMs — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
PEMT: Multi-Task Correlation Guided Mixture-of-Experts Enables Parameter-Efficient Transfer Learning — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
PORTULAN ExtraGLUE Datasets and Models: Kick-starting a Benchmark for the Neural Processing of Portuguese — 2024 · Proceedings of the 17th Workshop on Building and Using Comparable Corpora (BUCC) @ LREC-COLING 2024
Paraphrasing in Affirmative Terms Improves Negation Understanding — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Plausible Extractive Rationalization through Semi-Supervised Entailment Signal — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
RegMix: Data Mixture as Regression for Language Model Pre-training — 2024 · arXiv:2407.01492
Sparse MeZO: Less Parameters for Better Performance in Zeroth-Order LLM Fine-Tuning — 2024 · arXiv:2402.15751
Synthetic Multimodal Question Generation — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
Which Information Matters? Dissecting Human-written Multi-document Summaries with Partial Information Decomposition — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
Whispers of Doubt Amidst Echoes of Triumph in NLP Robustness — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
tasksource: A Large Collection of NLP tasks with a Structured Dataset Preprocessing Framework — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Étude des facteurs de complexité des modèles de langage dans une tâche de compréhension de lecture à l'aide d'une expérience contrôlée sémantiquement — 2024 · Actes de la 31ème Conférence sur le Traitement Automatique des Langues Naturelles, volume 1 : articles longs et prises de position
A Comprehensive Overview of Large Language Models — 2023 · arXiv:2307.06435
A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
ACES: Translation Accuracy Challenge Sets at WMT 2023 — 2023 · Proceedings of the Eighth Conference on Machine Translation
AD-KD: Attribution-Driven Knowledge Distillation for Language Model Compression — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)