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When Hard Negatives Hurt: Bridging the Generative-Discriminative Gap in Hard Negative Synthesis for Retrieval
Announce Type: replace Abstract: Hard negative mining has become the dominant strategy for training retrievers, yet it faces intrinsic limitations: negatives are bounded by corpus availability, selected by retriever score rather than diagnostic value, and increasingly contaminated by false positives as the retriever improves. LLM-based synthesis offers a principled alternative, where negatives that are unconstrained, targeted, and free from false positive risk. But we show that naively...
When Hard Negatives Hurt: Bridging the Generative-Discriminative Gap in Hard Negative Synthesis for Retrieval
arXiv:2606.01304v1 Announce Type: new Abstract: Hard negative mining has become the dominant strategy for training retrievers, yet it faces intrinsic limitations: negatives are bounded by corpus availability, selected by retriever score rather than diagnostic value, and increasingly contaminated by false positives as the retriever improves. LLM-based synthesis offers a principled alternative, where negatives that are unconstrained, targeted, and free from false positive risk. But we show...
Hard Labels In! Rethinking the Role of Hard Labels in Mitigating Local Semantic Drift
Announce Type: replace Abstract: Soft labels from teacher models are a de facto practice for knowledge transfer and large-scale dataset distillation (e.g., SRe2L, LPLD). However, when we limit the number of crops per image to reduce the substantial cost of storing precomputed soft labels, these methods suffer severely from local semantic drift: visually ambiguous crops can cause soft supervision to deviate from the image-level ground-truth semantics, leading to persistent errors and a...
How Hard Can It Be? Hardness-Aware Multi-Objective Unlearning
arXiv:2606.02119v1 Announce Type: new Abstract: Machine unlearning aims to remove the influence of specific forget training data due to privacy, copyright or bias concerns while maintaining the model performance on the remaining retain data. Existing unlearning algorithms, such as optimizing a weighted combination of losses, have tried to achieve these objectives of improving forget quality and maintaining retain utility. However, they do not guarantee that these objectives can be improved...
Trump makes pitch to farmers hard-hit by tariffs, high prices in Wisconsin
Trump makes pitch to farmers hard-hit by tariffs, high prices in Wisconsin Trump seeks to shore up support among rural voters hard hit by tariffs, economic fallout of war with Iran. United States President Donald Trump has sought to reassure farmers hard-hit by tariffs and the economic fallout of the US-Israeli war with Iran during a visit to Wisconsin. The stop in Chippewa Falls on Friday for a farming roundtable comes months before the midterm elections in November.
Trump pledges more Iran attacks, saying U.S. will be 'attacking them very hard'
US President Donald Trump speaks during a signing ceremony for the "Secure America Act" in the Oval Office of the White House in Washington, DC, on June 10, 2026. Ken Cedeno | Afp | Getty Images President Donald Trump said Wednesday that the U.S. would hit Iran "very hard" again, escalating his public threats as he pressed Tehran to sign a deal. "We hit them hard yesterday, and we're going to hit them hard again today," Trump said in televised remarks.
Towards Worst-case Hardness for Low-Noise LPN
Announce Type: new Abstract: The hardness of the Learning Parity with Noise (LPN) problem is a foundational assumption in cryptography, forming the basis of constructions ranging from symmetric-key primitives to public-key encryption and beyond. A central open question is whether the average-case hardness of LPN can be based on worst-case complexity assumptions, as has been achieved for the analogous Learning With Errors (LWE) problem. Existing worst-case-to-average-case reductions for LPN...
Chwalinska says years of hard work paid off in French Open run
Chwalinska says years of hard work paid off in French Open run PARIS, June 6 : Maja Chwalinska's remarkable French Open run ended in defeat in the final, but the Pole said her march was the culmination of 18 years of hard work finally clicking to carry her onto the biggest stage in Paris. Ranked 114 in the world before her three-week adventure began in the qualifying round, Chwalinska defeated higher-ranked opponents despite admittedly not being at her best, only to go down 6-3 6-2 to...
Middle East: US to hit Iran 'hard,' Trump says
Middle East: US to hit Iran 'hard,' Trump says Published June 10, 2026last updated June 10, 2026What you need to know - Trump says US will soon strike Iran 'very hard' amid escalating violence - UN secretary-general says there is a risk of a 'lesser fire' becoming a 'full war' - The US has blamed Iran for the crash of an attack helicopter off Oman and carried out strikes on Iranian sites - Iran has responded with attacks of its own on US sites in Bahrain and Kuwait - Trump says Iran must...
'Success of reforms and hard work Indians': PM Modi hails 7.7% GDP growth in FY26
Hailing India's 7.7% GDP growth in FY26, Prime Minister Narendra Modi on Friday said the expansion reflected the "inherent strength" of the economy, the "success of reforms" and the "hard work of 140 crore Indians". "India’s growth momentum remains strong! GDP growth rate of 7.7% in FY 2025-26 and 7.8% in Q4 of FY 2025-26 reflect the inherent strength of our economy, the success of reforms and the hard work of 140 crore Indians.