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title: "Who cites Adversarial NLI: A — page 2 — 659 citing papers"
description: "659 papers of the Elamur Research library cite «Adversarial NLI: A New Benchmark for Natural Language Understanding», found in their…"
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# Who cites «Adversarial NLI: A New Benchmark for Natural Language Understanding»

659 papers of our library cite it (of the 149,439 whose bibliographies we read) · 168 with a page here, the most cited first · page 2 of 2 · 101–168 · [← back to «Adversarial NLI: A New Benchmark for Natural Language Understanding»](https://md.research.elamur.ai/free/en/papers/nie-2020-adversarial-nli-new-benchmark-natural/)

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101. [**Auxiliary task demands mask the capabilities of smaller language models arXiv:2404.02418**Jennifer Hu, Michael C. Frank*2024 · 41 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-auxiliary-task-demands-mask-capabilities/)
102. **[A Systematic Survey of Automatic Prompt Optimization Techniques](https://md.research.elamur.ai/free/en/papers/ramnath-2025-systematic-survey-automatic-prompt-optimization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kiran Ramnath, Kang Zhou, Sheng Guan, et al.*2025 · 40 citations*
103. [**NOPE: A Corpus of Naturally-Occurring Presuppositions in English**Alicia Parrish, Sebastian Schuster, Alex Warstadt, et al.*2021 · 40 citations*](https://md.research.elamur.ai/free/en/papers/parrish-2021-nope-corpus-naturally-occurring-presuppositions/)
104. **[An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language Inference](https://md.research.elamur.ai/free/en/papers/liu-2020-empirical-study-model-agnostic-debiasing/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Tianyu Liu, Xin Zheng, Xiaoan Ding, et al.*2020 · 37 citations*
105. **[Distributed NLI: Learning to Predict Human Opinion Distributions for Language Reasoning](https://md.research.elamur.ai/free/en/papers/zhou-2022-distributed-nli-learning-predict-human/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiang Zhou, Yixin Nie, Mohit Bansal*2022 · 36 citations*
106. **[Mind the instructions: a holistic evaluation of consistency and interactions in prompt-based learning](https://md.research.elamur.ai/free/en/papers/weber-2023-mind-instructions-holistic-evaluation-consistency/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Lucas Weber, Elia Bruni, Dieuwke Hupkes*2023 · 29 citations*
107. **[HypoNLI: Exploring the Artificial Patterns of Hypothesis-only Bias in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/liu-2020-hyponli-exploring-artificial-patterns-hypothesis/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Tianyu Liu, Xin Zheng, Baobao Chang, et al.*2020 · 28 citations*
108. [**Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models arXiv:2310.00836**Man Luo, Shrinidhi Kumbhar, Ming shen, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-towards-logiglue-brief-survey-benchmark/)
109. **[New Protocols and Negative Results for Textual Entailment Data Collection](https://md.research.elamur.ai/free/en/papers/bowman-2020-new-protocols-negative-results-textual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Samuel R. Bowman, Jennimaria Palomaki, Livio Baldini Soares, et al.*2020 · 27 citations*
110. [**Understanding Retrieval Augmentation for Long-Form Question Answering arXiv:2310.12150**Hung-Ting Chen, Fangyuan Xu, Shane Arora, et al.*2023 · 24 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-understanding-retrieval-augmentation-long-form/)
111. [**Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models arXiv:2005.14709**Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/schlegel-2020-leaderboards-survey-methods-revealing-weaknesses/)
112. **[Compositionality and Sentence Meaning: Comparing Semantic Parsing and Transformers on a Challenging Sentence Similarity Dataset](https://md.research.elamur.ai/free/en/papers/fodor-2025-compositionality-sentence-meaning-comparing-semantic/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**James Fodor, Simon De Deyne, Shinsuke Suzuki*2025 · 22 citations*
113. [**Efficiently Adapting Pretrained Language Models To New Languages arXiv:2311.05741**Zoltan Csaki, Pian Pawakapan, Urmish Thakker, et al.*2023 · 21 citations*](https://md.research.elamur.ai/free/en/papers/csaki-2023-efficiently-adapting-pretrained-language-models/)
114. [**He Thinks He Knows Better than the Doctors: BERT for Event Factuality Fails on Pragmatics**Nanjiang Jiang, Marie-Catherine de Marneffe*2021 · 21 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2021-he-thinks-he-knows-better/)
115. **[Towards Effective Extraction and Evaluation of Factual Claims](https://md.research.elamur.ai/free/en/papers/metropolitansky-2025-effective-extraction-evaluation-factual-claims/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dasha Metropolitansky, Jonathan Larson*2025 · 20 citations*
116. [**Quality-Diversity through AI Feedback arXiv:2310.13032**Herbie Bradley, Andrew Dai, Hannah Teufel, et al.*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/bradley-2023-quality-diversity-through-ai-feedback/)
117. **[Diversity-oriented Data Augmentation with Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-diversity-oriented-data-augmentation-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zaitian Wang, Jinghan Zhang, Xinhao Zhang, et al.*2025 · 17 citations*
118. **[English Prompts are Better for NLI-based Zero-Shot Emotion Classification than Target-Language Prompts](https://md.research.elamur.ai/free/en/papers/barei-ss-2024-english-prompts-better-nli-based/) [ACM Web Conference (WWW)](https://md.research.elamur.ai/free/en/venues/acm-web-conference-www/)**Patrick Bareiß, Roman Klinger, Jeremy Barnes*2024 · 16 citations*
119. **[MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/park-2025-maporl-multi-agent-post-co/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chanwoo Park, Seungju Han, Xingzhi Guo, et al.*2025 · 15 citations*
120. **[Curing the SICK and Other NLI Maladies](https://md.research.elamur.ai/free/en/papers/kalouli-2023-curing-sick-other-nli-maladies/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Aikaterini-Lida Kalouli, Hai Hu, Alexander F. Webb, et al.*2023 · 14 citations*
121. **[Prompting for explanations improves Adversarial NLI. Is this true? \Yes\ it is \true\ because ıt weakens superficial cues\](https://md.research.elamur.ai/free/en/papers/kavumba-2023-prompting-explanations-improves-adversarial-nli/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pride Kavumba, Ana Brassard, Benjamin Heinzerling, et al.*2023 · 14 citations*
122. **[Integrating Transformers and Knowledge Graphs for Twitter Stance Detection](https://md.research.elamur.ai/free/en/papers/clark-2021-integrating-transformers-knowledge-graphs-twitter/) [Workshop on Noisy User-generated Text](https://md.research.elamur.ai/free/en/venues/wnut/)**Thomas Clark, Costanza Conforti, Fangyu Liu, et al.*2021 · 14 citations*
123. **[QCRD: Quality-guided Contrastive Rationale Distillation for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-qcrd-quality-guided-contrastive-rationale/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wei Wang, Zhaowei Li, Qi Xu, et al.*2025 · 13 citations*
124. [**The ICL Consistency Test arXiv:2312.04945**Lucas Weber, Elia Bruni, Dieuwke Hupkes*2023 · 12 citations*](https://md.research.elamur.ai/free/en/papers/weber-2023-icl-consistency-test/)
125. **[Learning from Diverse Reasoning Paths with Routing and Collaboration](https://md.research.elamur.ai/free/en/papers/lei-2025-learning-diverse-reasoning-paths-routing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhenyu Lei, Zhen Tan, Song Wang, et al.*2025 · 11 citations*
126. **[MEraser: An Effective Fingerprint Erasure Approach for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-meraser-effective-fingerprint-erasure-approach/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingxuan Zhang, Zhenhua Xu, Rui Hu, et al.*2025 · 11 citations*
127. **[Coreference Reasoning in Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/wu-2021-coreference-reasoning-machine-reading-comprehension/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingzhu Wu, Nafise Sadat Moosavi, Dan Roth, et al.*2021 · 11 citations*
128. **[EMO: Embedding Model Distillation via Intra-Model Relation and Optimal Transport Alignments](https://md.research.elamur.ai/free/en/papers/truong-2025-emo-embedding-model-distillation-intra/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Minh-Phuc Truong, Hai An Vu, Tu Vu, et al.*2025 · 10 citations*
129. **[How Often Are Errors in Natural Language Reasoning Due to Paraphrastic Variability?](https://md.research.elamur.ai/free/en/papers/srikanth-2024-how-often-are-errors-natural/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Neha Srikanth, Marine Carpuat, Rachel Rudinger*2024 · 10 citations*
130. **[FaithLM: Towards Faithful Explanations for Large Language Models](https://md.research.elamur.ai/free/en/papers/chuang-2026-faithlm-faithful-explanations-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, et al.*2026 · 9 citations*
131. **[A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI](https://md.research.elamur.ai/free/en/papers/chen-2025-rose-any-other-name-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Beiduo Chen, Siyao Peng, Anna Korhonen, et al.*2025 · 9 citations*
132. **[Zero-shot and Few-shot Learning with Instruction-following LLMs for Claim Matching in Automated Fact-checking](https://md.research.elamur.ai/free/en/papers/pisarevskaya-2025-zero-shot-few-shot-learning/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Dina Pisarevskaya, Arkaitz Zubiaga*2025 · 9 citations*
133. **[MSciNLI: A Diverse Benchmark for Scientific Natural Language Inference](https://md.research.elamur.ai/free/en/papers/sadat-2024-mscinli-diverse-benchmark-scientific-natural/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Mobashir Sadat, Cornelia Caragea*2024 · 9 citations*
134. **[PECO: Examining Single Sentence Label Leakage in Natural Language Inference Datasets through Progressive Evaluation of Cluster Outliers](https://md.research.elamur.ai/free/en/papers/saxon-2023-peco-examining-single-sentence-label/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Michael Saxon, Xinyi Wang, Wenda Xu, et al.*2023 · 9 citations*
135. **[Discourse-Driven Evaluation: Unveiling Factual Inconsistency in Long Document Summarization](https://md.research.elamur.ai/free/en/papers/zhong-2025-discourse-driven-evaluation-unveiling-factual/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yang Zhong, Diane Litman*2025 · 8 citations*
136. **[LiTEx: A Linguistic Taxonomy of Explanations for Understanding Within-Label Variation in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/hong-2025-litex-linguistic-taxonomy-explanations-understanding/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Pingjun Hong, Beiduo Chen, Siyao Peng, et al.*2025 · 8 citations*
137. [**Halu-J: Critique-Based Hallucination Judge arXiv:2407.12943**Binjie Wang, Steffi Chern, Ethan Chern, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-halu-j-critique-based-hallucination/)
138. [**GRIN: GRadient-INformed MoE arXiv:2409.12136**Liyuan Liu, Young Jin Kim, Shuohang Wang, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-grin-gradient-informed-moe/)
139. **[Simple but Challenging: Natural Language Inference Models Fail on Simple Sentences](https://md.research.elamur.ai/free/en/papers/luo-2022-simple-but-challenging-natural-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng Luo, Wei Liu, Jieyu Lin, et al.*2022 · 7 citations*
140. **[Entailed Between the Lines: Incorporating Implication into NLI](https://md.research.elamur.ai/free/en/papers/havaldar-2025-entailed-between-lines-incorporating-implication/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shreya Havaldar, Hamidreza Alvari, John Palowitch, et al.*2025 · 6 citations*
141. **[CTCC: A Robust and Stealthy Fingerprinting Framework for Large Language Models via Cross-Turn Contextual Correlation Backdoor](https://md.research.elamur.ai/free/en/papers/xu-2025-ctcc-robust-stealthy-fingerprinting-framework/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhenhua Xu, Xixiang Zhao, Xubin Yue, et al.*2025 · 4 citations*
142. **[Evaluating Numeracy of Language Models as a Natural Language Inference Task](https://md.research.elamur.ai/free/en/papers/mahendra-2025-evaluating-numeracy-language-models-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rahmad Mahendra, Damiano Spina, Lawrence Cavedon, et al.*2025 · 4 citations*
143. **[It is not True that Transformers are Inductive Learners: Probing NLI Models with External Negation](https://md.research.elamur.ai/free/en/papers/sullivan-2024-it-is-not-true-that/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Michael Sullivan*2024 · 4 citations*
144. **[Which Spurious Correlations Impact Reasoning in NLI Models? A Visual Interactive Diagnosis through Data-Constrained Counterfactuals](https://md.research.elamur.ai/free/en/papers/chan-2023-which-spurious-correlations-impact-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Robin Chan, Afra Amini, Mennatallah El-Assady*2023 · 4 citations*
145. **[FinNLI: Novel Dataset for Multi-Genre Financial Natural Language Inference Benchmarking](https://md.research.elamur.ai/free/en/papers/magomere-2025-finnli-novel-dataset-multi-genre/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jabez Magomere, Elena Kochkina, Samuel Mensah, et al.*2025 · 3 citations*
146. **[NLI under the Microscope: What Atomic Hypothesis Decomposition Reveals](https://md.research.elamur.ai/free/en/papers/srikanth-2025-nli-under-microscope-what-atomic/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Neha Srikanth, Rachel Rudinger*2025 · 3 citations*
147. **[How Hard is this Test Set? NLI Characterization by Exploiting Training Dynamics](https://md.research.elamur.ai/free/en/papers/cosma-2024-how-hard-is-this-test/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Adrian Cosma, Stefan Ruseti, Mihai Dascalu, et al.*2024 · 3 citations*
148. **[Pragmatic Reasoning Unlocks Quantifier Semantics for Foundation Models](https://md.research.elamur.ai/free/en/papers/li-2023-pragmatic-reasoning-unlocks-quantifier-semantics/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yiyuan Li, Rakesh Menon, Sayan Ghosh, et al.*2023 · 2 citations*
149. [**Synthetic Dataset for Evaluating Complex Compositional Knowledge for Natural Language Inference Proceedings of the 1st Workshop on Natural Language Reasoning and Structured Explanations (NLRSE)**Sushma Anand Akoju, Robert Vacareanu, Eduardo Blanco, et al.*2023 · 2 citations*](https://md.research.elamur.ai/free/en/papers/akoju-2023-synthetic-dataset-evaluating-complex-compositional/)
150. **[What does BERT Learn from Arabic Machine Reading Comprehension Datasets?](https://md.research.elamur.ai/free/en/papers/albilali-2021-what-does-bert-learn-arabic/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Eman Albilali, Nora Altwairesh, Manar Hosny*2021 · 2 citations*
151. **[FaithLens: Detecting and Explaining Faithfulness Hallucination](https://md.research.elamur.ai/free/en/papers/si-2026-faithlens-detecting-explaining-faithfulness-hallucination/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuzheng Si, Qingyi Wang, Haozhe Zhao, et al.*2026 · 1 citation*
152. **[FLUKE: A Linguistically-Driven and Task-Agnostic Framework for Robustness Evaluation](https://md.research.elamur.ai/free/en/papers/otmakhova-2026-fluke-linguistically-driven-task-agnostic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yulia Otmakhova, Thinh Hung Truong, Rahmad Mahendra, et al.*2026 · 1 citation*
153. **[Improving the OOD Performance of Closed-Source LLMs on NLI Through Strategic Data Selection](https://md.research.elamur.ai/free/en/papers/stacey-2026-improving-ood-performance-closed-source/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Joe Stacey, Lisa Alazraki, Aran Ubhi, et al.*2026 · 1 citation*
154. **[sutta at SemEval-2026 Task 12: A Multi-Perspective Retrieve-Verify-Aggregate Framework for Abductive Event Reasoning](https://md.research.elamur.ai/free/en/papers/zou-2026-sutta-semeval-2026-task-12/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Junliu Zou, Liang Yang, Jingjie Zeng*2026 · 1 citation*
155. **[On Reference (In-)Determinacy in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/chen-2025-reference-determinacy-natural-language-inference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sihao Chen, Chaitanya Malaviya, Alex Fabrikant, et al.*2025 · 1 citation*
156. [**Are Arabic Benchmarks Reliable? QIMMA's Quality-First Approach to LLM Evaluation arXiv:2604.03395**Leen AlQadi, Ahmed Alzubaidi, Mohammed Alyafeai, et al.*2026*](https://md.research.elamur.ai/free/en/papers/alqadi-2026-arabic-benchmarks-reliable-qimma-s/)
157. **[Assessing the Difficulty of Inference Types in Natural Language Inference for Clinical Trials](https://md.research.elamur.ai/free/en/papers/aguiar-2026-assessing-difficulty-inference-types-natural/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mathilde Aguiar, Pierre Zweigenbaum, Nona Naderi*2026*
158. **[Benchmarking LLM's Capability in Reasoning over Conflicting Web References](https://md.research.elamur.ai/free/en/papers/yuan-2026-benchmarking-llm-s-capability-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yizhen Yuan, Rui Kong, Dongze Li, et al.*2026*
159. **[ContextCheck: Sentence-Level Faithfulness Verification with Context-Aware Disambiguation](https://md.research.elamur.ai/free/en/papers/yin-2026-contextcheck-sentence-level-faithfulness-verification/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yueqin Yin, Yaxi Li, Xin Liu, et al.*2026*
160. **[Debiasing Logical Fallacy Detection for Real-World Robustness via Counterfactually Augmented Data](https://md.research.elamur.ai/free/en/papers/singh-2026-debiasing-logical-fallacy-detection-real/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Navyansh Singh*2026*
161. **[Measuring and Mitigating Shortcut Reliance in Language Models with Probe-Based Representation Entanglement](https://md.research.elamur.ai/free/en/papers/singh-2026-measuring-mitigating-shortcut-reliance-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Divyajot Singh*2026*
162. **[Mind's Eye: A Benchmark of Visual Abstraction, Transformation and Composition for Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/sinha-2026-mind-s-eye-benchmark-visual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rohit Sinha, Aditya Sanjiv Kanade, Sai Srinivas Kancheti, et al.*2026*
163. **[QueueEDIT: Structural Self-Correction for Sequential Model Editing in LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-queueedit-structural-self-correction-sequential/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Taolin Zhang, Haidong Kang, Dongyang Li, et al.*2026*
164. **[Soft Head Selection for Injecting ICL-Derived Task Embeddings](https://md.research.elamur.ai/free/en/papers/park-2026-soft-head-selection-injecting-icl/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jungwon Park, Jimyeong Kim, Changin Choi, et al.*2026*
165. **[VERICITE: Evaluating Sentence-Level Citation Faithfulness in Retrieval-Augmented Medical Question Answering](https://md.research.elamur.ai/free/en/papers/ma-2026-vericite-evaluating-sentence-level-citation/) [BioNLP](https://md.research.elamur.ai/free/en/venues/bionlp/)**Yixian Ma, Bohao Chu, Norbert Fuhr*2026*
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