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arXivU WashingtonThe University of Texas at AustiAllen Institute for Artificial IAlignment & preference optimization

Varying Shades of Wrong: Aligning LLMs with Wrong Answers Only

LLMs distinguish degrees of wrongness among incorrect answers, and alignment with such preferences yields less wrong answers and better calibration.

Jihan Yao, Wenxuan Ding, Shangbin Feng, Lucy Lu Wang and 1 more

Published Oct 14, 2024 · 0 citations · Code ★ 10

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11/20 AI panelreviewers recommend it

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AI panel: 11 of 20 reviewers recommend it
lenient 4/5
medium 5/10
strict 2/5
70%Highly rated
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NAACL 2024U WashingtonAllen Institute for Artificial ICarnegie MellonSummarization

P3Sum: Preserving Author’s Perspective in News Summarization with Diffusion Language Models

P3Sum uses diffusion language models to preserve authorial perspective in news summarization, outperforming autoregressive baselines on perspective fidelity.

Yuhan Liu, Shangbin Feng, Xiaochuang Han, Vidhisha Balachandran and 3 more

Published 2024 · 2 citations

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5/20 AI panelreviewers recommend it

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AI panel: 5 of 20 reviewers recommend it
lenient 3/5
medium 2/10
strict 0/5
72%Highly rated
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COLM 2024Washington University in St. LouAllen Institute for Artificial IInstruction tuning

LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition

LoraHub dynamically combines existing LoRA modules without extra parameters or gradients to generalize to unseen tasks with few examples, trading some accuracy for much lower inference token costs versus in-context learning.

Chengsong Huang, Qian Liu, Lin, Bill Yuchen, Tianyu Pang and 2 more

Published Jul 25, 2023 · 7 citations · ▲ 34 on Hugging Face · Code ★ 668

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8/20 AI panelreviewers recommend it

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AI panel: 8 of 20 reviewers recommend it
lenient 5/5
medium 3/10
strict 0/5
78%Highly rated
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EMNLP 2023FindingsU Notre DameU WashingtonAllen Institute for Artificial IXi'an JiaotongComputational social science

BotPercent: Estimating Bot Populations in Twitter Communities

BotPercent estimates community-specific Twitter bot populations by calibrating detection models across social contexts, revealing heterogeneous spatial-temporal bot distributions and achieving state-of-the-art community-level detection accuracy.

Zhaoxuan Tan, Shangbin Feng, Melanie Sclar, Herun Wan and 3 more

Published 2023 · 16 citations

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11/20 AI panelreviewers recommend it

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 0/5
86%Must read
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NeurIPS 2026SpotlightCMU, Carnegie MellonDepartment of Computer Science, U WashingtonGoogleU North Carolina at Chapel HillPose & motion

MolmoMotion: Forecasting Point Trajectories in 3D with Language Instruction

MolmoMotion predicts goal-conditioned 3D point trajectories from visual history and language, outperforming baselines on PointMotionBench and improving robot manipulation and video synthesis.

Jianing Zhang, Chenhao Zheng, Yajun Yang, Rustin Soraki and 6 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 53 on Hugging Face · Code ★ 151

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14/20 AI panelreviewers recommend it

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 2/5
80%Must read
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NeurIPS 2026Department of Computer Science, Allen Institute for Artificial IU Washington; MetaU WashingtonVisual grounding

Vision-Language Grounding as Bidirectional Concept Correspondence

Grounding is formulated as bidirectional concept correspondence to recover all image-text span correspondences without prespecified phrases via ConCor-1, improving F1 by 48% and 29% over baselines.

Jieyu Zhang, Ziqi Gao, Luke Zettlemoyer, Ranjay Krishna

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 6 on Hugging Face · Code ★ 8

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12/20 AI panelreviewers recommend it

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AI panel: 12 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 0/5